One of the most important issues discussed in Wireless Sensor Networks (WSNs) is how to transfer information from nodes within the network to the base station and select the best possible route for transmission of this information, taking into account energy consumption for the network lifetime with
maximum reliability and security. Hence, it would be useful to provide a suitable method that would have the features mentioned. This paper uses an Ad-hoc On-demand Multipath Distance Vector (AOMDV) as a routing protocol. This protocol has high energy consumption due to its multipath. However, it is a big challenge if it can reduce AOMDV energy consumption. Therefore, clustering operations for nodes are of high priority to determine the head of clusters which LEACH protocol and fuzzy logic and Particle Swarm Optimization (PSO) algorithm are used for this purpose. Simulation results represent 5% improvement in energy consumption in a WSN compared to AOMDV method.
GPS Enabled Energy Efficient Routing for ManetCSCJournals
In this paper, we propose an energy aware reactive approach by introducing energy and distance based threshold criteria. Cross Layer interaction is exploited the performance of physical layer which leads to significant improvement in the energy efficiency of a network.
ENERGY EFFICIENT ROUTING PROTOCOL BASED ON DSRijasuc
Energy consumption is a major concern in most of the present day devices in wireless networks. Especially
in Ad hoc networks, energy is a limited factor. Random movement in nodes add to the frequent failure of
routes which adds to the energy consumption in the network. In this paper, a routing protocol is proposed
which is based on a modification of the conventional DSR (Dynamic Source routing). A comparative
analysis is performed with respect to energy consumption, maximum throughput and delay. The routing
protocols used for reference in this analysis are DSDV, AODV and conventional DSR. Experimental results
show that the proposed modified DSR shows a reduced energy consumption, improved rate of maximum
throughput and a reduced delay compared to above mentioned routing protocols
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.
IMPROVEMENTS IN ROUTING ALGORITHMS TO ENHANCE LIFETIME OF WIRELESS SENSOR NET...IJCNCJournal
Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited
computation, communication, memory, and energy resources that are being used fora huge range of
applications. Clustering in WSNs is an effective way to minimize the energy consumption of sensor nodes.
In this paper improvements in various parameters are compared for three different routing algorithms.
First, it is started with Low Energy Adaptive Cluster Hierarchy (LEACH)which is a famed clustering
mechanism that elects a CH based on the probability model. Then, work describes a Fuzzy logic system
initiated CH selection algorithm for LEACH. Then Artificial Bee Colony (ABC)which is an optimisation
protocol owes its inspiration to the exploration behaviour of honey bees. In this study ABC optimization
algorithm is proposed for fuzzy rule selection. Then, the results of the three routing algorithms are
compared with respect to various parameters
AN OPTIMUM ENERGY CONSUMPTION HYBRID ALGORITHM FOR XLN STRATEGIC DESIGN IN WSN’SIJCNCJournal
In this paper, X-Layer protocol is originated which executes mobility error prediction (MEP) algorithm to calculate the remaining energy level of each node. This X-Layer protocol structure employs the mobility aware protocol that senses the mobility concerned to each node with the utilization of Ad-hoc On-Demand Distance Vector (AODV), which shares the information or data specific to the distance among individual nodes. With the help of this theory, the neighbour list will be updated only to those nodes which are mobile resulting in less energy consumption when compared to all (static/mobile) other nodes in the network. Apart from the MEP algorithm, clustering head (CH) election algorithm has also been specified to identify the relevant clusters whether they exists within the network region or not. Also clustering multi-hop routing (CMHR) algorithm was implemented in which the node can identify the cluster to which it belongs depending upon the distance from each cluster surrounding the node. Finally comprising the AODV routing protocol with the Two-Ray Ground method, we implement X-Layer protocol structure by considering MAC protocol in accordance to IEEE 802.15.4 to obtain the best results in energy consumption and also by reducing the energy wastage with respect to each node. The effective results had been illustrated through Network Simulator-II platform.
Performance Evaluation of Consumed Energy-Type-Aware Routing (CETAR) For Wire...ijwmn
This work evaluates the performance of Consumed-Energy-Type-Aware Routing (CETAR) which incorporates the amount of energy consumed per type of operation for routing decision to extend the lifetime of the Wireless Sensor Networks (WSNs). CETAR makes routing decision using statistics of the energy consumed for each type of node activities including sensing, data processing, data transmission as a source node, and routing operations. In particular, CETAR encourages a node which seldom plays a role of source node as a routing node to preserve the energy of active source nodes to prolong the functionality of the WSNs. Extensive simulation study demonstrates that the lifetime of the Geographic and Energy Aware Routing (GEAR) can be significantly extended with CETAR. With its adaptability to deployed sensor node behaviors, the significance of CETAR to extend the lifetime of WSNs is clear.
Recent Developments in Routing Algorithms for Achieving Elongated Life in WSNijsrd.com
Battery life is a key issue for an elongated life in WSN. Clustering of nodes is done to achieve the energy conservation in LEACH algorithm. The main objectives of clustering are equal distribution of energy and equal distribution of nodes in space so that less energy is consumed and early deaths of nodes can be delayed. In LEACH both of these objectives can’t be achieved. Further Max-Energy LEACH is able to achieve energy equi-distribution but not the space equi-distribution because CH can be selected from one region only leading to large energy consumption by nodes to send data to CHs. The clustering algorithm while doing its work should pay attention toward the number of nodes a cluster is having. If we can equi-distribute all nodes to cluster then we assume that it may lead to better energy efficiency. This paper discusses the recent developments in WSN in this direction.
GPS Enabled Energy Efficient Routing for ManetCSCJournals
In this paper, we propose an energy aware reactive approach by introducing energy and distance based threshold criteria. Cross Layer interaction is exploited the performance of physical layer which leads to significant improvement in the energy efficiency of a network.
ENERGY EFFICIENT ROUTING PROTOCOL BASED ON DSRijasuc
Energy consumption is a major concern in most of the present day devices in wireless networks. Especially
in Ad hoc networks, energy is a limited factor. Random movement in nodes add to the frequent failure of
routes which adds to the energy consumption in the network. In this paper, a routing protocol is proposed
which is based on a modification of the conventional DSR (Dynamic Source routing). A comparative
analysis is performed with respect to energy consumption, maximum throughput and delay. The routing
protocols used for reference in this analysis are DSDV, AODV and conventional DSR. Experimental results
show that the proposed modified DSR shows a reduced energy consumption, improved rate of maximum
throughput and a reduced delay compared to above mentioned routing protocols
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.
IMPROVEMENTS IN ROUTING ALGORITHMS TO ENHANCE LIFETIME OF WIRELESS SENSOR NET...IJCNCJournal
Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited
computation, communication, memory, and energy resources that are being used fora huge range of
applications. Clustering in WSNs is an effective way to minimize the energy consumption of sensor nodes.
In this paper improvements in various parameters are compared for three different routing algorithms.
First, it is started with Low Energy Adaptive Cluster Hierarchy (LEACH)which is a famed clustering
mechanism that elects a CH based on the probability model. Then, work describes a Fuzzy logic system
initiated CH selection algorithm for LEACH. Then Artificial Bee Colony (ABC)which is an optimisation
protocol owes its inspiration to the exploration behaviour of honey bees. In this study ABC optimization
algorithm is proposed for fuzzy rule selection. Then, the results of the three routing algorithms are
compared with respect to various parameters
AN OPTIMUM ENERGY CONSUMPTION HYBRID ALGORITHM FOR XLN STRATEGIC DESIGN IN WSN’SIJCNCJournal
In this paper, X-Layer protocol is originated which executes mobility error prediction (MEP) algorithm to calculate the remaining energy level of each node. This X-Layer protocol structure employs the mobility aware protocol that senses the mobility concerned to each node with the utilization of Ad-hoc On-Demand Distance Vector (AODV), which shares the information or data specific to the distance among individual nodes. With the help of this theory, the neighbour list will be updated only to those nodes which are mobile resulting in less energy consumption when compared to all (static/mobile) other nodes in the network. Apart from the MEP algorithm, clustering head (CH) election algorithm has also been specified to identify the relevant clusters whether they exists within the network region or not. Also clustering multi-hop routing (CMHR) algorithm was implemented in which the node can identify the cluster to which it belongs depending upon the distance from each cluster surrounding the node. Finally comprising the AODV routing protocol with the Two-Ray Ground method, we implement X-Layer protocol structure by considering MAC protocol in accordance to IEEE 802.15.4 to obtain the best results in energy consumption and also by reducing the energy wastage with respect to each node. The effective results had been illustrated through Network Simulator-II platform.
Performance Evaluation of Consumed Energy-Type-Aware Routing (CETAR) For Wire...ijwmn
This work evaluates the performance of Consumed-Energy-Type-Aware Routing (CETAR) which incorporates the amount of energy consumed per type of operation for routing decision to extend the lifetime of the Wireless Sensor Networks (WSNs). CETAR makes routing decision using statistics of the energy consumed for each type of node activities including sensing, data processing, data transmission as a source node, and routing operations. In particular, CETAR encourages a node which seldom plays a role of source node as a routing node to preserve the energy of active source nodes to prolong the functionality of the WSNs. Extensive simulation study demonstrates that the lifetime of the Geographic and Energy Aware Routing (GEAR) can be significantly extended with CETAR. With its adaptability to deployed sensor node behaviors, the significance of CETAR to extend the lifetime of WSNs is clear.
Recent Developments in Routing Algorithms for Achieving Elongated Life in WSNijsrd.com
Battery life is a key issue for an elongated life in WSN. Clustering of nodes is done to achieve the energy conservation in LEACH algorithm. The main objectives of clustering are equal distribution of energy and equal distribution of nodes in space so that less energy is consumed and early deaths of nodes can be delayed. In LEACH both of these objectives can’t be achieved. Further Max-Energy LEACH is able to achieve energy equi-distribution but not the space equi-distribution because CH can be selected from one region only leading to large energy consumption by nodes to send data to CHs. The clustering algorithm while doing its work should pay attention toward the number of nodes a cluster is having. If we can equi-distribute all nodes to cluster then we assume that it may lead to better energy efficiency. This paper discusses the recent developments in WSN in this direction.
A MIN-MAX SCHEDULING LOAD BALANCED APPROACH TO ENHANCE ENERGY EFFICIENCY AND ...IJCNCJournal
Energy efficiency and traffic management in Mobile Ad hoc Networks (MANETs) is a complex process due
to the self-organizing nature of the nodes. Quality of service (QoS) of the network is achieved by
addressing the issues concerned with load handling and energy conservation. This manuscript proposes a
min-max scheduling (M2S) algorithm for energy efficiency and load balancing (LB) in MANETs. The
algorithm operates in two phases: neighbor selection and load balancing. In state selection, the
transmission of the node is altered based on its energy and packet delivery factor. In the load balancing
phase, the selected nodes are induced by queuing and scheduling the process to improve the rate of load
dissemination. The different processes are intended to improve the packet delivery factor (PDF) by
selecting appropriate node transmission states. The transmission states of the nodes are classified through
periodic remaining energy update; the queuing and scheduling process is dynamically adjusted with energy
consideration. A weight-based normalized function eases neighbor selection by determining the most
precise neighbor that satisfies transmission and energy constraints. The results of the proposed M2SLB
(Min-Max Scheduling Load Balancing) proves the consistency of the proposed algorithm by improving the
network throughput, packet delivery ratio and minimizing delay and packet loss by retaining higher
remaining energy.
G-DEEC: GATEWAY BASED MULTI-HOP DISTRIBUTED ENERGY EFFICIENT CLUSTERING PROTO...IJCI JOURNAL
Wireless sensor network is composed of hundreds and thousands of small wireless sensor nodes which
collect information by sensing the physical environment. The sensed data is processed and communicated
to other sensor nodes and finally to Base Station. So energy efficient routing to final destination called base
station is ongoing current requirement in wireless sensor networks. Here in this research paper we propose
a multi-hop DEEC routing scheme i.e. G-DEEC for heterogeneous networks where we deploy rechargeable
intermediate nodes called gateways in-between cluster head and base station for minimizing energy
consumption by sensor nodes in each processing round thereby increasing the network lifetime and
stability of wireless sensor networks unlike DEEC.
ENERGY EFFICIENT DIRECTION BASED ROUTING PROTOCOL FOR WSNIAEME Publication
Energy consumption is one of the limitations in Wireless Sensor Networks (WSNs). The routing protocols are the hot areas to address quality-of-service (QoS) related issues viz. Energy consumption, network lifetime, network scalability and packet overhead. The key issue in WSN is that these networks suffer from the packet overhead, which is the core cause of more energy consumption and damage the QoS in sensor networks. In WSN, there are several routing protocols which are used to improve the performance of the network. Out of those protocols, Dynamic Source Routing (DSR) protocol is more appropriate in terms of small energy density, but sometimes when the mode of a node changes from active to sleep, the effectiveness decreases as the data packets needs to wait at the initial point where the packet has been sent and this increases the waiting time and end to end interruption of the packets which leads to increase in energy consumption. Our problem is to recognize the dead nodes and to choose another suitable path so that the data transmission becomes smoother and less energy gets preserved. In order to resolve these issues, we propose directional transmission-based energy aware routing protocol named as PDORP. The proposed protocol PDORP has the characteristics of both Power Efficient Gathering Sensor Information System (PEGASIS) and DSR routing protocols. In addition, hybridization of Genetic Algorithm (GA) and Bacterial Foraging Optimization (BFO) is applied to proposed routing protocol to identify energy efficient optimal paths. The performance analysis, comparison through a hybridization approach of the proposed routing protocol gives better result comprising less bit error rate, less delay, less energy ingesting and better throughput which leads to better QoS and prolong the lifetime
Q-LEARNING BASED ROUTING PROTOCOL TO ENHANCE NETWORK LIFETIME IN WSNSIJCNCJournal
In resource constraint Wireless Sensor Networks (WSNs), enhancement of network lifetime has been one of the significantly challenging issues for the researchers. Researchers have been exploiting machine learning techniques, in particular reinforcement learning, to achieve efficient solutions in the domain of WSN. The objective of this paper is to apply Q-learning, a reinforcement learning technique, to enhance the lifetime of the network, by developing distributed routing protocols. Q-learning is an attractive choice for routing due to its low computational requirements and additional memory demands. To facilitate an agent running at each node to take an optimal action, the approach considers node’s residual energy, hop length to sink and transmission power. The parameters, residual energy and hop length, are used to calculate the Q-value, which in turn is used to decide the optimal next-hop for routing. The proposed protocols’ performance is evaluated through NS3 simulations, and compared with AODV protocol in terms of network lifetime, throughput and end-to-end delay.
Genetic-fuzzy based load balanced protocol for WSNsIJECEIAES
Recent advancement in wireless sensor networks primarily depends upon energy constraint. Clustering is the most effective energy-efficient technique to provide robust, fault-tolerant and also enhance network lifetime and coverage. Selection of optimal number of cluster heads and balancing the load of cluster heads are most challenging issues. Evolutionary based approach and soft computing approach are best suitable for counter the above problems rather than mathematical approach. In this paper we propose hybrid technique where Genetic algorithm is used for the selection of optimal number of cluster heads and their fitness value of chromosome to give optimal number of cluster head and minimizing the energy consumption is provided with the help of fuzzy logic approach. Finally cluster heads uses multi-hop routing based on A*(A-star) algorithm to send aggregated data to base station which additionally balance the load. Comparative study among LEACH, CHEF, LEACH-ERE, GAEEP shows that our proposed algorithm outperform in the area of total energy consumption with various rounds and network lifetime, number of node alive versus rounds and packet delivery or packet drop ratio over the rounds, also able to balances the load at cluster head.
Energy balanced improved leach routing protocol for wireless sensor networkscsandit
A proper sensor node clustering is an effective topology control that can balance energy
consumption among sensor nodes and increase network scalability and life time. As the use of
wireless sensor networks (WSNs) has grown enormously, the need for energy-efficient routing
and data aggregation has also risen. LEACH
(
Low Energy Adaptive Cluster Hierarchy
)
is a
hierarchical clustering protocol that provides an elegant solution for such protocols. Random
clustering is the main deficiency of LEACH. In this paper an energy balanced clustering
approach is proposed, in which the K-mean clustering algorithm is applied. It is centralized
clustering algorithm that based on minimum energy clustering to form optimal clusters. For the
candidate nodes, the location and the residual energy are used as key parameters to select the
cluster head (CH). The method shows that the proposed approach outperforms LEACH in terms
of energy conservation and network life time prolonging.
Performance evaluation of hierarchical clustering protocols with fuzzy C-means IJECEIAES
The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.
A RELIABLE AND ENERGY EFFICIENCT ROUTING PROTOCOL FOR MANETs cscpconf
A mobile ad-hoc network (MANETs) is an infrastructure less network in which the mobile nodes
communicate with each other. Due to its various characteristics like highly dynamic topology
and limited battery power of the nodes, routing is one of the key issue. Also, it is not possible to
give a significant amount of power to the mobile nodes of ad-hoc networks. Because of all this
the energy consumption is also an important issue. Due to limited battery power, some other
issues like if some node gets fail, which results in loss of data packets and no reliable data
transfer has been raised. In this paper, an algorithm is proposed for data transmission which
detects the node failure (due to energy) before it actually happens. Because of this network
lifetime gets improved. The proposed routing algorithm is energy efficient as compared to
AODV routing algorithm. The performance is analyzed on the basis of various performance
metrics like Energy Consumption, Packet Delivery Ratio, Network Life Time, Network Routing
Overhead and number of Exhausted nodes in the network by using the NS2 Simulator.
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
Energy balanced on demand clustering algorithm based on leach-cijwmn
As the use of Wireless Sensor Networks (WSNs) has grown enormously, the need for energy-efficient management has also risen. With advances in ubiquitous computing environment, WSNs have been broadly studied and many energy-efficient routing protocols had been proposed. LEACH (Low Energy Adaptive Clustering Hierarchy) is a popular cluster-based protocol, which provides distributed adaptive clustering and periodic cluster head (CH) selection rotation. As extension to LEACH, LEACH-C (LEACH Centralized) was proposed, in which the energy is utilized to select CH. However, both can’t guarantee cluster head distribution, in addition to considerable periodic clustering overhead. Furthermore, network topology change is a critical characteristic that has influence on communication path and load distribution among nodes. To resolve such problems, Energy-Balance on Demand Clustering Algorithm Based on LEACH-C is proposed. The algorithm adopts centralized cluster formation and distributed CH selection methods. Minimum energy clustering is used to divide the network into clusters, while energy and total communication distance are considered as secondary criteria to select optimal CH. From simulation results the proposed algorithm outperforms LEACH-C in life time, stability period and performance efficiency.
PERFORMANCE ANALYSIS IN CELLULAR NETWORKS CONSIDERING THE QOS BY RETRIAL QUEU...IJCNCJournal
In this article, a retrial queueing model will be considered with persevering customers for wireless cellular
networks which can be frequently applied in the Fractional Guard Channel (FGC) policies, including
Limited FGC (LFGC), Uniform FGC (UFGC), Limited Average FGC (LAFGC) and Quasi Uniform FGC
(QUFGC). In this model, the examination on the retrial phenomena permits the analyses of important
effectiveness measures pertained to the standard of services undergone by users with the probability that a
fresh call first arrives the system and find all busy channels at the time, the probability that a fresh call
arrives the system from the orbit and find all busy channels at the time and the probability that a handover
call arrives the system and find all busy channels at the time. Comparison between four types of the FGC
policy can befound to evaluate the performance of the system.
The hierarchical routing of data in WSNs is a specific class of routing protocols it encompasses solutions that take a restructuring of the physical network in a logical hierarchy system for the optimization of the consum-ption of energy. Several hierarchical routing solutions proposed, namely: the protocol LEACH (Low Energy Adaptive Clustering Hierarchy) consist of dividing the network in distributed clusters at one pop in order of faster data delivery and PEGASIS protocol (Power-Efficient Gathering in Sensor Information Systems) which uses the principle of constructing a chain’s sensor node. Our contribution consists of a hierarchical routing protocol, which is the minimization of the energy consumption by reducing the transmission distance of data and reducing the data delivery time. Our solution combines the two hierarchical routing approaches: chain based approach and the cluster based approach. Our approach allows for multi-hop communications, intra- and intercluster, and a collaborative aggregation of data in each Cluster, and a collaborative aggregation of data at each sensor node.
SECTOR TREE-BASED CLUSTERING FOR ENERGY EFFICIENT ROUTING PROTOCOL IN HETEROG...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
An Adaptive Energy Aware Clustering Based Reliable Routing for in-Network Agg...Editor IJCATR
Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or
environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more
imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC
algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed
protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval
process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based
selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is
identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely
covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves
imbalanced among cluster head and improve the network life time.
Energy Aware Routing Protocol for Energy Constrained Mobile Ad-hoc Networks IJECEIAES
Dynamic topology change and decentralized makes routing a challenging task in mobile ad hoc network. Energy efficient routing is the most challenging task in MANET due to limited energy of mobile nodes. Limited power of batteries typically use in MANET, and this is not easy to change or replace while running communication. Network disorder can occur for many factors but in middle of these factors deficiency of energy is the most significant one for causing broken links and early partition of the network. Evenly distribution of power between nodes could enhance the lifetime of the network, which leads to improving overall network transmission and minimizes the connection request. To discourse this issue, we propose an Energy Aware Routing Protocol (EARP) which considers node energy in route searching process and chooses nodes with higher energy levels. The EARP aim is to establish t he shortest route from source to destination that contains energy efficient nodes. The performance of EARP is evaluated in terms of packet delivery ratio, network lifetime, end-to-end delay and throughput. Results of simulation done by using NS2 network simulator shows that EARP can achieve both high throughput and delivery ratio, whereas increase network lifetime and decreases end-to-end delay.
Cluster Based Routing using Energy and Distance Aware Multi-Objective Golden ...IJCNCJournal
In recent years, WSNs have attracted significant attention due to the improvements in various sectors such as communication, electronics, and information technologies. When the clustering algorithm incorporates both Euclidean distance and energy, it automatically decreases the energy consumption. So, the major goal of this research is to reduce energy consumption for prolong the lifetime of the network. In order to achieve an energy-efficient process, Energy and Distance Aware Multi-Objective Golden Eagle Optimization (ED-MOGEO) is proposed in this research. In addition, this proposed solution reduces retransmissions and delays to improve the performance metrics. And so, this research carried out two major fitness functions (Euclidean distance and energy) for creating an energy-efficient WSN. Furthermore, energy consideration is used to reduce the nodes unavailability which results in packet loss during the transmission. For generating the routing path between the source and the Base Station (BS), the ED-MOGEO algorithm is used. From the simulation results, it shows that Proposed ED-MOGEO achieves better performances in terms of residual energy (14.36 J), end-to-end delay (12.9 ms), packet delivery ratio (0.994), normalized routing overhead (0.11), and throughput (1.131 Mbps) when compared to existing Cluster-Based Data Aggregation (CBDA) and Elephant Herding Optimization (EHO)-Greedy methods.
CLUSTER BASED ROUTING USING ENERGY AND DISTANCE AWARE MULTI-OBJECTIVE GOLDEN ...IJCNCJournal
In recent years, WSNs have attracted significant attention due to the improvements in various sectors such
as communication, electronics, and information technologies. When the clustering algorithm incorporates
both Euclidean distance and energy, it automatically decreases the energy consumption. So, the major goal
of this research is to reduce energy consumption for prolong the lifetime of the network. In order to
achieve an energy-efficient process, Energy and Distance Aware Multi-Objective Golden Eagle
Optimization (ED-MOGEO) is proposed in this research. In addition, this proposed solution reduces
retransmissions and delays to improve the performance metrics. And so, this research carried out two
major fitness functions (Euclidean distance and energy) for creating an energy-efficient WSN.
Furthermore, energy consideration is used to reduce the nodes unavailability which results in packet loss
during the transmission. For generating the routing path between the source and the Base Station (BS), the
ED-MOGEO algorithm is used. From the simulation results, it shows that Proposed ED-MOGEO achieves
better performances in terms of residual energy (14.36 J), end-to-end delay (12.9 ms), packet delivery ratio
(0.994), normalized routing overhead (0.11), and throughput (1.131 Mbps) when compared to existing
Cluster-Based Data Aggregation (CBDA) and Elephant Herding Optimization (EHO)-Greedy methods.
OPTIMIZED CLUSTER ESTABLISHMENT AND CLUSTER-HEAD SELECTION APPROACH IN WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
Optimized Cluster Establishment and Cluster-Head Selection Approach in WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
A MIN-MAX SCHEDULING LOAD BALANCED APPROACH TO ENHANCE ENERGY EFFICIENCY AND ...IJCNCJournal
Energy efficiency and traffic management in Mobile Ad hoc Networks (MANETs) is a complex process due
to the self-organizing nature of the nodes. Quality of service (QoS) of the network is achieved by
addressing the issues concerned with load handling and energy conservation. This manuscript proposes a
min-max scheduling (M2S) algorithm for energy efficiency and load balancing (LB) in MANETs. The
algorithm operates in two phases: neighbor selection and load balancing. In state selection, the
transmission of the node is altered based on its energy and packet delivery factor. In the load balancing
phase, the selected nodes are induced by queuing and scheduling the process to improve the rate of load
dissemination. The different processes are intended to improve the packet delivery factor (PDF) by
selecting appropriate node transmission states. The transmission states of the nodes are classified through
periodic remaining energy update; the queuing and scheduling process is dynamically adjusted with energy
consideration. A weight-based normalized function eases neighbor selection by determining the most
precise neighbor that satisfies transmission and energy constraints. The results of the proposed M2SLB
(Min-Max Scheduling Load Balancing) proves the consistency of the proposed algorithm by improving the
network throughput, packet delivery ratio and minimizing delay and packet loss by retaining higher
remaining energy.
G-DEEC: GATEWAY BASED MULTI-HOP DISTRIBUTED ENERGY EFFICIENT CLUSTERING PROTO...IJCI JOURNAL
Wireless sensor network is composed of hundreds and thousands of small wireless sensor nodes which
collect information by sensing the physical environment. The sensed data is processed and communicated
to other sensor nodes and finally to Base Station. So energy efficient routing to final destination called base
station is ongoing current requirement in wireless sensor networks. Here in this research paper we propose
a multi-hop DEEC routing scheme i.e. G-DEEC for heterogeneous networks where we deploy rechargeable
intermediate nodes called gateways in-between cluster head and base station for minimizing energy
consumption by sensor nodes in each processing round thereby increasing the network lifetime and
stability of wireless sensor networks unlike DEEC.
ENERGY EFFICIENT DIRECTION BASED ROUTING PROTOCOL FOR WSNIAEME Publication
Energy consumption is one of the limitations in Wireless Sensor Networks (WSNs). The routing protocols are the hot areas to address quality-of-service (QoS) related issues viz. Energy consumption, network lifetime, network scalability and packet overhead. The key issue in WSN is that these networks suffer from the packet overhead, which is the core cause of more energy consumption and damage the QoS in sensor networks. In WSN, there are several routing protocols which are used to improve the performance of the network. Out of those protocols, Dynamic Source Routing (DSR) protocol is more appropriate in terms of small energy density, but sometimes when the mode of a node changes from active to sleep, the effectiveness decreases as the data packets needs to wait at the initial point where the packet has been sent and this increases the waiting time and end to end interruption of the packets which leads to increase in energy consumption. Our problem is to recognize the dead nodes and to choose another suitable path so that the data transmission becomes smoother and less energy gets preserved. In order to resolve these issues, we propose directional transmission-based energy aware routing protocol named as PDORP. The proposed protocol PDORP has the characteristics of both Power Efficient Gathering Sensor Information System (PEGASIS) and DSR routing protocols. In addition, hybridization of Genetic Algorithm (GA) and Bacterial Foraging Optimization (BFO) is applied to proposed routing protocol to identify energy efficient optimal paths. The performance analysis, comparison through a hybridization approach of the proposed routing protocol gives better result comprising less bit error rate, less delay, less energy ingesting and better throughput which leads to better QoS and prolong the lifetime
Q-LEARNING BASED ROUTING PROTOCOL TO ENHANCE NETWORK LIFETIME IN WSNSIJCNCJournal
In resource constraint Wireless Sensor Networks (WSNs), enhancement of network lifetime has been one of the significantly challenging issues for the researchers. Researchers have been exploiting machine learning techniques, in particular reinforcement learning, to achieve efficient solutions in the domain of WSN. The objective of this paper is to apply Q-learning, a reinforcement learning technique, to enhance the lifetime of the network, by developing distributed routing protocols. Q-learning is an attractive choice for routing due to its low computational requirements and additional memory demands. To facilitate an agent running at each node to take an optimal action, the approach considers node’s residual energy, hop length to sink and transmission power. The parameters, residual energy and hop length, are used to calculate the Q-value, which in turn is used to decide the optimal next-hop for routing. The proposed protocols’ performance is evaluated through NS3 simulations, and compared with AODV protocol in terms of network lifetime, throughput and end-to-end delay.
Genetic-fuzzy based load balanced protocol for WSNsIJECEIAES
Recent advancement in wireless sensor networks primarily depends upon energy constraint. Clustering is the most effective energy-efficient technique to provide robust, fault-tolerant and also enhance network lifetime and coverage. Selection of optimal number of cluster heads and balancing the load of cluster heads are most challenging issues. Evolutionary based approach and soft computing approach are best suitable for counter the above problems rather than mathematical approach. In this paper we propose hybrid technique where Genetic algorithm is used for the selection of optimal number of cluster heads and their fitness value of chromosome to give optimal number of cluster head and minimizing the energy consumption is provided with the help of fuzzy logic approach. Finally cluster heads uses multi-hop routing based on A*(A-star) algorithm to send aggregated data to base station which additionally balance the load. Comparative study among LEACH, CHEF, LEACH-ERE, GAEEP shows that our proposed algorithm outperform in the area of total energy consumption with various rounds and network lifetime, number of node alive versus rounds and packet delivery or packet drop ratio over the rounds, also able to balances the load at cluster head.
Energy balanced improved leach routing protocol for wireless sensor networkscsandit
A proper sensor node clustering is an effective topology control that can balance energy
consumption among sensor nodes and increase network scalability and life time. As the use of
wireless sensor networks (WSNs) has grown enormously, the need for energy-efficient routing
and data aggregation has also risen. LEACH
(
Low Energy Adaptive Cluster Hierarchy
)
is a
hierarchical clustering protocol that provides an elegant solution for such protocols. Random
clustering is the main deficiency of LEACH. In this paper an energy balanced clustering
approach is proposed, in which the K-mean clustering algorithm is applied. It is centralized
clustering algorithm that based on minimum energy clustering to form optimal clusters. For the
candidate nodes, the location and the residual energy are used as key parameters to select the
cluster head (CH). The method shows that the proposed approach outperforms LEACH in terms
of energy conservation and network life time prolonging.
Performance evaluation of hierarchical clustering protocols with fuzzy C-means IJECEIAES
The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.
A RELIABLE AND ENERGY EFFICIENCT ROUTING PROTOCOL FOR MANETs cscpconf
A mobile ad-hoc network (MANETs) is an infrastructure less network in which the mobile nodes
communicate with each other. Due to its various characteristics like highly dynamic topology
and limited battery power of the nodes, routing is one of the key issue. Also, it is not possible to
give a significant amount of power to the mobile nodes of ad-hoc networks. Because of all this
the energy consumption is also an important issue. Due to limited battery power, some other
issues like if some node gets fail, which results in loss of data packets and no reliable data
transfer has been raised. In this paper, an algorithm is proposed for data transmission which
detects the node failure (due to energy) before it actually happens. Because of this network
lifetime gets improved. The proposed routing algorithm is energy efficient as compared to
AODV routing algorithm. The performance is analyzed on the basis of various performance
metrics like Energy Consumption, Packet Delivery Ratio, Network Life Time, Network Routing
Overhead and number of Exhausted nodes in the network by using the NS2 Simulator.
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
Energy balanced on demand clustering algorithm based on leach-cijwmn
As the use of Wireless Sensor Networks (WSNs) has grown enormously, the need for energy-efficient management has also risen. With advances in ubiquitous computing environment, WSNs have been broadly studied and many energy-efficient routing protocols had been proposed. LEACH (Low Energy Adaptive Clustering Hierarchy) is a popular cluster-based protocol, which provides distributed adaptive clustering and periodic cluster head (CH) selection rotation. As extension to LEACH, LEACH-C (LEACH Centralized) was proposed, in which the energy is utilized to select CH. However, both can’t guarantee cluster head distribution, in addition to considerable periodic clustering overhead. Furthermore, network topology change is a critical characteristic that has influence on communication path and load distribution among nodes. To resolve such problems, Energy-Balance on Demand Clustering Algorithm Based on LEACH-C is proposed. The algorithm adopts centralized cluster formation and distributed CH selection methods. Minimum energy clustering is used to divide the network into clusters, while energy and total communication distance are considered as secondary criteria to select optimal CH. From simulation results the proposed algorithm outperforms LEACH-C in life time, stability period and performance efficiency.
PERFORMANCE ANALYSIS IN CELLULAR NETWORKS CONSIDERING THE QOS BY RETRIAL QUEU...IJCNCJournal
In this article, a retrial queueing model will be considered with persevering customers for wireless cellular
networks which can be frequently applied in the Fractional Guard Channel (FGC) policies, including
Limited FGC (LFGC), Uniform FGC (UFGC), Limited Average FGC (LAFGC) and Quasi Uniform FGC
(QUFGC). In this model, the examination on the retrial phenomena permits the analyses of important
effectiveness measures pertained to the standard of services undergone by users with the probability that a
fresh call first arrives the system and find all busy channels at the time, the probability that a fresh call
arrives the system from the orbit and find all busy channels at the time and the probability that a handover
call arrives the system and find all busy channels at the time. Comparison between four types of the FGC
policy can befound to evaluate the performance of the system.
The hierarchical routing of data in WSNs is a specific class of routing protocols it encompasses solutions that take a restructuring of the physical network in a logical hierarchy system for the optimization of the consum-ption of energy. Several hierarchical routing solutions proposed, namely: the protocol LEACH (Low Energy Adaptive Clustering Hierarchy) consist of dividing the network in distributed clusters at one pop in order of faster data delivery and PEGASIS protocol (Power-Efficient Gathering in Sensor Information Systems) which uses the principle of constructing a chain’s sensor node. Our contribution consists of a hierarchical routing protocol, which is the minimization of the energy consumption by reducing the transmission distance of data and reducing the data delivery time. Our solution combines the two hierarchical routing approaches: chain based approach and the cluster based approach. Our approach allows for multi-hop communications, intra- and intercluster, and a collaborative aggregation of data in each Cluster, and a collaborative aggregation of data at each sensor node.
SECTOR TREE-BASED CLUSTERING FOR ENERGY EFFICIENT ROUTING PROTOCOL IN HETEROG...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
An Adaptive Energy Aware Clustering Based Reliable Routing for in-Network Agg...Editor IJCATR
Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or
environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more
imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC
algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed
protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval
process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based
selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is
identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely
covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves
imbalanced among cluster head and improve the network life time.
Energy Aware Routing Protocol for Energy Constrained Mobile Ad-hoc Networks IJECEIAES
Dynamic topology change and decentralized makes routing a challenging task in mobile ad hoc network. Energy efficient routing is the most challenging task in MANET due to limited energy of mobile nodes. Limited power of batteries typically use in MANET, and this is not easy to change or replace while running communication. Network disorder can occur for many factors but in middle of these factors deficiency of energy is the most significant one for causing broken links and early partition of the network. Evenly distribution of power between nodes could enhance the lifetime of the network, which leads to improving overall network transmission and minimizes the connection request. To discourse this issue, we propose an Energy Aware Routing Protocol (EARP) which considers node energy in route searching process and chooses nodes with higher energy levels. The EARP aim is to establish t he shortest route from source to destination that contains energy efficient nodes. The performance of EARP is evaluated in terms of packet delivery ratio, network lifetime, end-to-end delay and throughput. Results of simulation done by using NS2 network simulator shows that EARP can achieve both high throughput and delivery ratio, whereas increase network lifetime and decreases end-to-end delay.
Cluster Based Routing using Energy and Distance Aware Multi-Objective Golden ...IJCNCJournal
In recent years, WSNs have attracted significant attention due to the improvements in various sectors such as communication, electronics, and information technologies. When the clustering algorithm incorporates both Euclidean distance and energy, it automatically decreases the energy consumption. So, the major goal of this research is to reduce energy consumption for prolong the lifetime of the network. In order to achieve an energy-efficient process, Energy and Distance Aware Multi-Objective Golden Eagle Optimization (ED-MOGEO) is proposed in this research. In addition, this proposed solution reduces retransmissions and delays to improve the performance metrics. And so, this research carried out two major fitness functions (Euclidean distance and energy) for creating an energy-efficient WSN. Furthermore, energy consideration is used to reduce the nodes unavailability which results in packet loss during the transmission. For generating the routing path between the source and the Base Station (BS), the ED-MOGEO algorithm is used. From the simulation results, it shows that Proposed ED-MOGEO achieves better performances in terms of residual energy (14.36 J), end-to-end delay (12.9 ms), packet delivery ratio (0.994), normalized routing overhead (0.11), and throughput (1.131 Mbps) when compared to existing Cluster-Based Data Aggregation (CBDA) and Elephant Herding Optimization (EHO)-Greedy methods.
CLUSTER BASED ROUTING USING ENERGY AND DISTANCE AWARE MULTI-OBJECTIVE GOLDEN ...IJCNCJournal
In recent years, WSNs have attracted significant attention due to the improvements in various sectors such
as communication, electronics, and information technologies. When the clustering algorithm incorporates
both Euclidean distance and energy, it automatically decreases the energy consumption. So, the major goal
of this research is to reduce energy consumption for prolong the lifetime of the network. In order to
achieve an energy-efficient process, Energy and Distance Aware Multi-Objective Golden Eagle
Optimization (ED-MOGEO) is proposed in this research. In addition, this proposed solution reduces
retransmissions and delays to improve the performance metrics. And so, this research carried out two
major fitness functions (Euclidean distance and energy) for creating an energy-efficient WSN.
Furthermore, energy consideration is used to reduce the nodes unavailability which results in packet loss
during the transmission. For generating the routing path between the source and the Base Station (BS), the
ED-MOGEO algorithm is used. From the simulation results, it shows that Proposed ED-MOGEO achieves
better performances in terms of residual energy (14.36 J), end-to-end delay (12.9 ms), packet delivery ratio
(0.994), normalized routing overhead (0.11), and throughput (1.131 Mbps) when compared to existing
Cluster-Based Data Aggregation (CBDA) and Elephant Herding Optimization (EHO)-Greedy methods.
OPTIMIZED CLUSTER ESTABLISHMENT AND CLUSTER-HEAD SELECTION APPROACH IN WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
Optimized Cluster Establishment and Cluster-Head Selection Approach in WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
MULTICASTING BASED ENHANCED PROACTIVE SOURCE ROUTING IN MANETSIJCNCJournal
Mobile Ad-hoc Network (MANET) is an accumulation of movable nodes organizing a irregular topology without centralized administration. In a MANET, multicasting is a significant technique for utilizing data communication system. Multicasting based enhanced proactive source routing is proposed in this paper for Mobile Ad hoc Networks. It explains an innovative multicasting algorithm that considers the transmission energy and residual energy while forwarding the data packets. It improves the network throughput and raises the network lifetimes. Simulation analysis is carried in this proposed system and this method shows improved performance over the existing system.
Energy efficiency has recently turned out to be primary issue in wireless sensor networks.
Sensor networks are battery powered, therefore become dead after a certain period of time. Thus,
improving the data dissipation in energy efficient way becomes more challenging problem in order to
improve the lifetime for sensor devices. The clustering and tree based data aggregation for sensor
networks can enhance the network lifetime of wireless sensor networks. Non-dominated Sorting Genetic
Algorithm (NSGA) -III based energy efficient clustering and tree based routing protocol is proposed.
Initially, clusters are formed on the basis of remaining energy, then, NSGA-III based data aggregation
will come in action to improve the inter-cluster data aggregation further. Extensive analysis demonstrates
that proposed protocol considerably enhances network lifetime over other techniques.
ENERGY EFFICIENT ROUTING PROTOCOL BASED ON DSRijasuc
Energy consumption is a major concern in most of the present day devices in wireless networks. Especially
in Ad hoc networks, energy is a limited factor. Random movement in nodes add to the frequent failure of
routes which adds to the energy consumption in the network. In this paper, a routing protocol is proposed
which is based on a modification of the conventional DSR (Dynamic Source routing). A comparative
analysis is performed with respect to energy consumption, maximum throughput and delay. The routing
protocols used for reference in this analysis are DSDV, AODV and conventional DSR. Experimental results
show that the proposed modified DSR shows a reduced energy consumption, improved rate of maximum
throughput and a reduced delay compared to above mentioned routing protocols.
ENERGY EFFICIENT DIRECTION BASED ROUTING PROTOCOL FOR WSNIAEME Publication
Energy consumption is one of the limitations in Wireless Sensor Networks (WSNs). The routing protocols are the hot areas to address quality-of-service (QoS) related issues viz. Energy consumption, network lifetime, network scalability and packet overhead. The key issue in WSN is that these networks suffer from the packet overhead, which is the core cause of more energy consumption and damage the QoS in sensor networks. In WSN, there are several routing protocols which are used to improve the performance of the network. Out of those protocols, Dynamic Source Routing (DSR) protocol is more appropriate in terms of small energy density, but sometimes when the mode of a node changes from active to sleep, the effectiveness decreases as the data packets needs to wait at the initial point where the packet has been sent and this increases the waiting time and end to end interruption of the packets which leads to increase in energy consumption. Our problem is to recognize the dead nodes and to choose another suitable path so that the data transmission becomes smoother and less energy gets preserved. In order to resolve these issues, we propose directional transmission-based energy aware routing protocol named as PDORP. The proposed protocol PDORP has the characteristics of both Power Efficient Gathering Sensor Information System (PEGASIS) and DSR routing protocols. In addition, hybridization of Genetic Algorithm (GA) and Bacterial Foraging Optimization (BFO) is applied to proposed routing protocol to identify energy efficient optimal paths. The performance analysis, comparison through a hybridization approach of the proposed routing protocol gives better result comprising less bit error rate, less delay, less energy ingesting and better throughput which leads to better QoS and prolong the lifetime
AN EXTENDED K-MEANS CLUSTER HEAD SELECTION ALGORITHM FOR EFFICIENT ENERGY CON...IJNSA Journal
Effective use of sensor nodes’ batteries in wireless sensor networks is critical since the batteries are difficult to recharge or replace. This is closely connected to the networks’ lifespan since once the battery is used up, the node is no longer useful. The entire network will not function if 60 to 80% of the nodes in it have completely depleted their energy. In order to minimize energy usage and sustain the network for a long time, many cluster head selection algorithms have been developed. However, the existing cluster head selection algorithms such as K-Means, particle swarm selection optimization (PSO), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Fuzzy C-Means (FCM) cluster head election algorithm have not fully reduced the issue of energy usage in WSN. The objective of this paper was to develop an extended K Mean Cluster Head selection(CHS) algorithm that uses remaining energy, distance between node and base station, distance between nodes and neighbour nodes, node density, node degree Maximum Cluster size, received signal strength indicator (RSSI) and Signal to Noise Ratio. The algorithm developed was used to enhance the lifespan of WSNs. The performance of the simulated variants of LEACH routing protocols is measured and evaluated using the quantitative research methodology. Utilizing residual node energy, packet delivery ratio, throughput, network longevity, average energy usage, and the number of live and dead node, the suggested approach is contrasted to previous approaches. From the study we observed that the proposed approach outperforms existing actual LEACH, Mod-LEACH and TSILEACH approaches.
Routing Optimization with Load Balancing: an Energy Efficient ApproachEswar Publications
The area of Wireless Sensor Network (WSN) is covered with considerable range of problems, where majority of research attempts were carried out to enhance the network lifetime of WSN. But very few of the studies have proved successful. This manuscript discusses about a structure for optimizing routing and load balancing that uses standard radio and energy model to perform energy optimization by introducing a novel routing agent. The routing agent is built within aggregator node and base station to perform self motivated reconfiguration in case of energy depletion. Compared with standard LEACH algorithm, the proposed technique has better energy efficiency within optimal data aggregation duration.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy
Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy
Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
ENERGY-BALANCED IMPROVED LEACH ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKScscpconf
A proper sensor node clustering is an effective topology control that can balance energy
consumption among sensor nodes and increase network scalability and life time. As the use of
wireless sensor networks (WSNs) has grown enormously, the need for energy-efficient routing
and data aggregation has also risen. LEACH
(
Low Energy Adaptive Cluster Hierarchy
)
is a
hierarchical clustering protocol that provides an elegant solution for such protocols. Random
clustering is the main deficiency of LEACH. In this paper an energy balanced clustering
approach is proposed, in which the K-mean clustering algorithm is applied. It is centralized
clustering algorithm that based on minimum energy clustering to form optimal clusters. For the
candidate nodes, the location and the residual energy are used as key parameters to select the
cluster head (CH). The method shows that the proposed approach outperforms LEACH in terms
of energy conservation and network life time prolonging.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
Similar to IMPROVEMENT of MULTIPLE ROUTING BASED on FUZZY CLUSTERING and PSO ALGORITHM IN WSNS TO REDUCE ENERGY CONSUMPTION (20)
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
** Connect, Collaborate, And Innovate: IJCNC - Where Networking Futures Take ...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Top 10 Oil and Gas Projects in Saudi Arabia 2024.pdf
IMPROVEMENT of MULTIPLE ROUTING BASED on FUZZY CLUSTERING and PSO ALGORITHM IN WSNS TO REDUCE ENERGY CONSUMPTION
1. International Journal of Computer Networks & Communications (IJCNC) Vol.10, No.6, November 2018
DOI: 10.5121/ijcnc.2018.10606 97
IMPROVEMENT of MULTIPLE ROUTING BASED on
FUZZY CLUSTERING and PSO ALGORITHM IN WSNS
TO REDUCE ENERGY CONSUMPTION
Gholamreza Farahani
Department of Electrical Engineering and Information Technology, Iranian Research
Organization for Science and Technology (IROST), Tehran, Iran
ABSTRACT
One of the most important issues discussed in Wireless Sensor Networks (WSNs) is how to transfer
information from nodes within the network to the base station and select the best possible route for
transmission of this information, taking into account energy consumption for the network lifetime with
maximum reliability and security. Hence, it would be useful to provide a suitable method that would have
the features mentioned. This paper uses an Ad-hoc On-demand Multipath Distance Vector (AOMDV) as a
routing protocol. This protocol has high energy consumption due to its multipath. However, it is a big
challenge if it can reduce AOMDV energy consumption. Therefore, clustering operations for nodes are of
high priority to determine the head of clusters which LEACH protocol and fuzzy logic and Particle Swarm
Optimization (PSO) algorithm are used for this purpose. Simulation results represent 5% improvement in
energy consumption in a WSN compared to AOMDV method.
KEYWORDS
Energy Aware Routing Protocol, Fuzzy Logic, Ad-hoc Multipath, LEACH, Particle Swarm Optimization
Algorithm
1. INTRODUCTION
The use of WSNs in a variety of sectors, such as military, industrial, agriculture, medicine, etc. is
a unique feature of the world today due to its ease of use.
The deployment of nodes in a random or predefined manner in a specified two-dimensional or
three-dimensional form as sensor nodes for gathering information creates a WSN. One of the
issues that is considered a challenge in WSNs is the routing issue, along with reducing energy
consumption. So far, various mechanisms have been introduced to collect, send and process data
in WSN. One of these operation mechanisms is network clustering. Clustering is one of the
methods used to collect and send packets in a WSN. This operation has advantages such as
system scalability, increased network lifetime, and reduced redundancy in sending and consuming
energy. Choosing the cluster head in clustering nodes is an important step, because clustering
requires energy consumption and may be wasted a lot of energy. One of the most famous
protocols in clustering is LEACH [1].
As discussed, routing should be aware of energy usage. One of the routing protocols is the Ad-
hoc On-demand Distance Vector (AODV) [2], which has high power consumption due to its
multipath and multichannel packet sending during routing time. In order to improve the efficiency
of the AODV protocol, a method called the AOMDV is proposed [3], the most important effect
2. International Journal of Computer Networks & Communications (IJCNC) Vol.10, No.6, November 2018
98
being the addition of multipath capability in the AODV classical protocol. The introduction of
node states to enhance the AODV's efficiency in selecting the main path is an important goal of
this new protocol. In the path discovery process, the rules for updating the route will calculate the
node's weight for each path, as well as sorting the path size in descending order in the list of
paths, and a route will choose that provide more path weight for data transfer. There is also the
use of Route Request (RREQ) packet delay to send packets on the network as well as the
threshold of energy to simplify network congestion. Therefore, evolutionary methods need to be
developed to solve this problem in order to improve the energy consumption for the longer
lifetime of nodes and ultimately the network [4].
In this paper, a method for energy aware routing in WSN will be presented. In the proposed
method, fuzzy logic and PSO algorithm are used to improve the AOMDV routing protocol and
the LEACH clustering protocol, and a new routing scheme with minimum energy consumption is
proposed.
In the field of WSNs energy aware routing, there are many studies. In DAM et al. [5] and Kevin
[6], pipeline and power techniques are suggested for cryptosystem to reduce power consumption.
In addition, it is expected to increase the level of security and achieve high performance that
makes it suitable for uninterrupted applications, as discussed in Nguyen et al. [7].
In Rages and Baskaran [8], estimating the lifetime of a Body WSN with use of probabilistic
analysis and Monte Carlo simulation is proposed. This framework makes possible to control the
uninterrupted health of patients with wearable vital signal wireless sensors. In the control of
health, the loss of critical or emergency information is a serious issue. Therefore, ensuring the
quality of service provision is essential. It is important to have an estimated lifetime of the
network to replace or change batteries because the loss of important information is not acceptable.
The lifetime of the body WSN is defined as the duration of the failure of the first node due to
battery drain. The heart rate and blood glucose levels are controlled in a centralized location in a
health / medical environment managed to evaluate the performance of the physical WSN.
In the other research, in Singh and Verma [9], a homogeneous protocol has been presented that is
sensitive to the optimal energy consumption distributed on the adaptive threshold based on the
middle layer routing protocol. In this research, probabilistic weight is assigned to cluster heads of
each cluster from the network, and the purpose of the research is to provide a new protocol for
reducing distributed energy consumption during routing.
Ke et al. [10] has proposed a hierarchical clustering approach to reduce energy consumption in
the WSN during routing, which named the proposed protocol as novel energy-aware hierarchical
cluster-based (NEACH).
Yigit et al. [11] has presented channel aware routing and the multichannel timing priority for
routing is used. Channel selection is carried out during routing time with minimizing energy
consumption. The use of a Link-Quality-Aware Routing Algorithm (LQ-CMST) along with the
Priority and Channel-Aware Multi-Channel (PCA-MC) for intelligent WSN applications are
considered.
In [12], the base station is considered as the Region of Interest (ROI). The simultaneous use of
two protocols, called On-Hole Children Reconnection (OHCR) and On-Hole Alert (OHA), with
their distributed natural properties, can solve the power consumption problem in remote locations.
Two mentioned protocols have been identified using two Degree Constraint Tree (DCT) and
Shortest Path Tree (SPT) that has been able to contribute up to 50% to energy storage.
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Vimalarani et al. [13] proposed an Enhanced PSO-Based Clustering Energy Optimization (EPSO-
CEO) algorithm for WSN in which clustering and clustering head selection are done by using
PSO algorithm with respect to minimizing the power consumption in WSN.
Some researches focus on the metaheuristic methods. Kuila and Jana [14] are proposed
Linear/Nonlinear Programming (LP/NLP) formulations of energy efficient clustering and routing
followed by two algorithms for the same based on PSO. The routing algorithm is developed with
an efficient particle encoding scheme and multi-objective fitness function. The clustering
algorithm is presented by considering energy conservation of the nodes through load balancing.
The results of algorithms demonstrate their superiority in terms of network life, energy
consumption, dead sensor nodes and delivery of total data packets to the base station in
comparison with other methods.
Balaji et al. [15] presented a fuzzy based PSO routing technique to improve the network
scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve
the uncertainty and network balancing. Cluster heads are calculated using PSO algorithm to
reduce the energy consumption. Their simulation results show that the proposed routing protocol
can perform load balancing effectively and reduce the energy consumption of cluster heads.
In other recent research, a Trust-Based Secure Routing (TBSR) scheme using the traceback
approach has been proposed to improve the security of data routing and maximize the use of
available energy in Energy-Harvesting WSNs (EHWSNs) [16].
Fardin Far and Alaei [17] are proposed a method to increase the efficiency of the Optimized Link
State Routing Protocol (OLSR) [18] by generating new parameters and considering the amount of
nodes energy. They have selected the optimal route based on the remained energy in the middle
nodes, the distance between the nodes and the number of steps with use of the Genetic algorithm-
based approach for optimal routing in the OLSR protocol.
An Energy-Balanced Routing Protocol (EBRP) for WSNs is proposed in [19]. In EBRP, the
network is divided into several clusters by using K-means++ algorithm [20] and select the cluster
head by using the Fuzzy Logical System (FLS). To get the fuzzy rules for different networks,
Genetic Algorithm (GA) is used. EBRP compared with the routing protocols such as LEACH,
Low-Energy Adaptive Clustering Hierarchy-Centralized (LEACH-C) [21], and Stable Election
Protocol (SEP) [22], which prolongs the network lifetime (first node dies) by 57%, 63%, and
63%, respectively.
Kamran Khan et al. [23] proposed routing algorithm for the transmission of data, cluster head
selection algorithm, and a scheme for the formation of clusters named Energy-Efficient
Multistage Routing Protocol (EE-MRP). Based on the energy analysis of the existing routing
protocols, they proposed a multistage data transmission mechanism. They adopted an efficient
cluster head selection algorithm and exterminated unnecessary frequency of reclustering. Static
clustering is used for efficient selection of cluster heads. They compared the performance and
energy efficiency of their routing protocol with other routing protocols and observed their routing
protocol (EE-MRP) has performed well in terms of overall network lifetime, throughput, and
energy efficiency.
Other research uses a geographic routing protocol to route the packets. The geographic routing
protocol route packets in a hop-by-hop way, where a node selects a relay node to forward packets
among the neighboring nodes based on the geographic location information of the neighboring
nodes. To employ geographic routing protocols, two neighboring nodes need to exchange the
location information with each other periodically. In a mobile ad hoc network, however, a packet
transmitted between two neighboring nodes may be lost due to the out-of-date location
information, which result in demanding extra energy to retransmit the packet.
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Tang et al. [24] by considering the out-of-date neighboring location information, proposed two
methods capable of augmenting geographic routing protocols to reduce energy consumption in
mobile ad hoc networks. The first one uses a tradeoff between the progress distance and the
energy consumption when selecting a relay node. The second one uses energy consumption when
selecting a relay node, to consume minimum energy to route a packet between a source-
destination pair in the continuous domain. Their results shown method of Tang can reduce the
energy consumption while preserving the high packet delivery rate.
Also, to exchange energy-efficient messages among neighboring nodes, the reactive type EAO
(Energy-Aware One-to-one routing) [25] and LEU (Low-Energy Unicast Ad-hoc routing) [26]
protocols are proposed to unicast messages to the destination node. In the EAO protocol, the total
electric energy of nodes and delay time from a source node to a destination node can be reduced
compared with the ESU [27] and AODV protocols. However, a source-to-destination route may
not be found if the communication range of each node is shorter.
To solve this problem IEAO (Improved Energy-Aware One-to-one routing) protocol [28] is
proposed. In IEAO protocol, after a shortest route is found to the destination node, a more energy-
efficient prior node is found in nearest neighbor of each node starting from the destination node.
Therefore, a neighbor node which has an uncovered neighbor node is selected as a prior node for
each node to make a route.
At continuation of paper in section 2, model of the system is explained, then section 3 will
describe the proposed method. Simulation results are presented in section 4 and finally section 5
concludes the paper.
2. MODEL OF SYSTEM
In this section, first, some definitions and models to calculate power consumption in WSN is
explained.
2.1. Definition
a) Sensing range
It is range that a sensor can sense a particular area. As shown in figure 1, a sensing range of
sensor S is a circle with radius r.
Figure 1. Sensing range of sensor S is inside of circle with radius r
b) Communication range
It is range that sensor can communicate with another sensor.
c) Degree of coverage
When an area is covered by a sensor S, then the degree of coverage of that area is one because it is covered
within the sensing range of only one sensor.
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2.2. Condition of intersection
If two sensors S1 and S2 are considered. Both two sensors are intersect with each other when sum
of radius is less than and equal to distance between centers. Therefore, following condition could
be raised.
a) Case 1: Two sensors sensing range has intersection (figure 2).
Figure 2. Two sensors S1 and S2 sensing range has intersected with each other
b) Case 2: Two sensors sensing range has touch without creating any intersection area (figure 3).
Figure 3. Two sensors S1 and S2 sensing range has touch with each other
c) Two sensor sensing range separate with each other (figure 4).
Figure 4. Two sensors S1 and S2 sensing range separate with each other
d) One sensor is within another sensor sensing range (figure 5).
Figure 5. Two sensors S1 and S2 have intersect with each other
2.3. Determination of intersection area
To calculate intersection area, according to figure 6, the two following equations should be
solved.
(1)2 2
( 1) 1x y+ − =
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(2)2 2
( 1) 1x y− + =
Figure 6. Two intersect S1 and S2 sensors
If the line y=x is drawn on the graph, the intersection area will split into two equal pieces (figure
7).
Figure 7. Two equal pieces of intersection area
Now, notice that we can form a triangle in the S1 circle, from the dashed line to the center at
(1,1). It will be a 45º-45º-90º right triangle (figure 7).
The area of quarter of the circle with radius 1 is π/4 and the area of the triangle is 1/2. Therefore,
the area of S1 circle above the line y=x is as equation (3).
(3)1 ( 2)
4 2 4
π π −
− =
The equation (3) is half of the intersection area, therefore, the entire intersection area is:
(4)1 ( 2)
2 ( )
4 2 2
π π −
× − =
Thus, the intersection area on the case of radius for both sensing range equal 1 is calculated. If
radius of sensing range of sensors equal with r, the intersection area with be as equation (5).
(5)2( 2)
2
r
π −
×
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3. PROPOSED METHOD
In this section, the proposed algorithm to reduce energy consumption in WSN will explain.
Initially, a series of points and positions are defined by default, so that sensor nodes can be
identified and replace at routing time. It should be noted that all of the sensor nodes deployed at
the default points are fixed and are in fact static. The base station, announcing the target and
targets calculate the remaining energy in each round through equation (6) and then maintain the
remaining energy.
(6)( ) [ ( )] /i iV t Initial E t r= −
In equation (6), Initial is the initial energy, ( )iE t is the energy of node and r is the current cycle.
It should consider a region for sensing. If there are two s1 and s2 sensors, both of these sensors
intersect with each other when the total radius of the area is less than and equal to the distance
between each center in of that area and its relation is given by equation (7) (figure 2).
(7)2 2
1 2 2 1 2 1( ) ( )r r x x y y+ ≤ − + −
As can be seen in equation (7), the Euclidean distance is considered that r1 is the first sensing
range radius, r2 is the secondary sensing range radius, (x1 ,y1) and (x2,y2) are coordinates in the
Cartesian system for S1 and S2 sensors respectively.
There are several special cases that should be investigated. When the sensing range from one
sensor to another sensor is separated, there is equation (8).
(8)1 2 1 2Distance( , )s s r r> +
When a sensor is located within the sensing range of another sensor, there will be equation (9).
(9)1 2 1 2Distance( , )s s r r< +
When two sensors are only touched, without creating an intersected area, the equation (10) will
exist.
(10)1 2 1 2Distance( , )s s r r= +
Considering the three conditions of the equations (8) to (10) is vital. It is also important to
determine the area for intersection the sensing range of sensing nodes. When the sensing range of
the sensors cross each other, a zone will create in the form of equation (11).
(11)1 2 1 2 1 2 1 2- Distance( , ) , wherer r s s r r r r< < + >
After specifying the intersected area, the degree of coverage for the AODMV protocol settings
can be determined for multipath. When the two sensing range of sensors intersected with each
other, their coverage is equal to one that is defined by the definition of the coverage. The
relationship between the degree of coverage for the two sensors s1 and s2 is a proven equation (12)
[29].
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(12)
1 2 1 2 1 2 2 1 1 2
1 2 1 2 1 2 1 2
( ) then 1 1
2 2 2 2 1 2 2
if s s x s s s s s s s s x x x
x x s s x s s s s x s s s s
= = − + − + = − + − +
→ − + = → − = → − = → − =
I U I
U U U U I
If a sensor covers a region, the coverage degree will be equal to one, and if two sensors cover a
region, the coverage degree of that area will be equal to 2, which is calculated from the proven
equation (13) [29].
(13)1 2 1 2 1 2 1 1 2 0 1 2 0s s s s s s s s= + − = + − = → =U I U
By replacing equation (13) is equation (12), will result equation (14).
(14)1 2 2s s =I
Now after finding the intersected area between nodes of WSN, the AOMDV protocol is
considered as a multipath method and a clustering operation is performed. The purpose of using
fuzzy logic in the paper is to identify and distinguish cluster patterns in the network. First, a
known node will select as a cluster head. The cluster head collects other information and sends it
to the central station. The cluster head functions like a local central station sensor. Selection of
the cluster in this paper is carried out with the help of fuzzy membership functions and fuzzy
rules. Therefore, in order to better distribute the load between the sensor nodes, the same cluster
that includes the cluster head, will be used.
In the network, there are several clusters, each with a cluster head, and each node belongs to a
cluster that is geographically distributed throughout the network. Cluster head is used to increase
network life and reduce energy consumption. The cluster is dynamically selected according to its
energy.
The default protocol in clustering and choosing the cluster head is LEACH that fuzzification is
carried out on it. The AOMDV protocol consists of two steps, clustering, and scheduling for
nodes that operate on packet transmissions in the network, and each node produces a random
number between 0 and 1.
The nodes that have values below the threshold are selected as the cluster head. Hence, due to the
uncertainty, a fuzzy relation can be considered for nodes (Equation (15)).
(15)
( ) ,
mod 1
1 .
p
T N if n G
r
p
p
= →
−
In equation (15), p is a value that checks if the node has cluster head condition. r is the number of
cycles to select the cluster head and G is a set of nodes that are not selected as cluster heads.
Initially, the network area is divided into two regions, called region 1 and region 2, which nodes
in region 1 have a higher probability to select as a cluster head. It should be noted that the base
station is located as a fixed area in the center of the network region. The base station calculates
the distance from the sink node to compare with threshold value (equation (16) derived from
equation (12)).
(16)( )( )2 2
2TR a b= − +
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where TR is the threshold and a and b are coordinated in the Cartesian system. In equation (16),
nodes whose distance is greater than the threshold will discard, and the node that is near the
center with less energy is chosen as the sink node.
In the proposed method, the two AOMDV and LEACH protocols will fuzzy simultaneously. Two
important parameters that are used as fuzzy inputs to select the cluster head in the AOMDV
protocol are the energy level and the center of the node in a set with respect to its neighboring
nodes and two other important input parameters for the LEACH protocol, are amount of energy
consumed in the packet sending path that is used by the node and the number of steps in the path.
Calculation of energy consumption for each cluster and the packet sending path is critical to
minimizing energy consumption. The two parameters of the AOMDV protocol are updated at the
request of the packet from one node to the other node in a cluster or outside the cluster. Then the
first node that has the destination path sends two values of the LEACH protocol for clustering and
packet response on the network.
Until the node for sending respond is not on the destination, there will be a packet request in the
network until it reaches the destination. This is due to determination the amount of energy
consumed on the path. Then the output results of the fuzzy segment will be the input of the
routing section for the AOMDV protocol again, which will first find the optimal route, and
second, the least amount of energy will be consumed.
The number of nodes in each path other than the source node and destination node is known as a
step. After clustering and choosing a cluster head based on fuzzy logic and LEACH and AOMDV
algorithms, an optimization algorithm is required to improve the routing of the AOMDV protocol.
Hence, PSO algorithm is used with regard to its advantages. Perhaps one of the most important
reasons for using the PSO algorithm is the high convergence rate compared to other evolutionary
algorithms. The best value to improve energy consumption in the routing process is named bestP
and the best position ever known by the particle population is named bestG . After finding the best
values, the velocity and position of each particle are updated using equations (17) and (18),
respectively.
(17)[ ] [ ] [ ] [ ]( ) [ ] [ ]( )1 2() ()best bestv particles v i C rand P position i C rand G position i= + × × − + × × −
(18)[ ] [ ] [ ]1position i position i v i+ = +
where v[] is the particle velocity, position[] is the current particle (solution), rand () is a random
number between (0,1) and C1, C2 are learning factors. usually C1 = C2 = 2.
The right side of equation (17) consists of three parts: the first part is the current velocity of the
particle, and the second and third parts are particle velocity change and its rotation towards the
best personal experience and best experience of the group.
If the first part of equation (17) is not taken into account, then the particle velocity is determined
only by the current position and the best experience of the particle and the best group experience.
In this way, the best particle of the group stays in place and the others move toward that particle.
In fact, the mass movement of particles without the first part of Equation (17) will be a process in
which the search space gradually becomes small and a local search around the best particle forms.
In contrast, if only the first part of equation (17) is taken into account, particles will go their own
way to reach the boundary wall and perform a kind of global search.
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The convergence rate is another important issue in the PSO algorithm. Several methods have been
proposed to increase the convergence speed of the optimal particle swarm algorithm. This scheme
usually involves changes to the PSO algorithm update equations, without altering the structure of
the algorithm. Therefore, there is usually a better result in local optimization performance, which
is sometimes carried out with a slight change in functional performance.
One of the advances in PSO algorithm is the use of weight inertia. The weight inertia is a factor in
scaling the speed associated with the previous step. As a result, a new equation for updating
speeds can be found in equation (19).
(19)( ) ( )1 1 2 2( ). ( 1) ( 1) ( 1)i i i iw t V t C r P X t C r g X t− + × × − − + × × − −
Considering the results of the PSO algorithm, w(t) has been considered in the interval [0, 1.4], but
over time, the results of the experiments show that there is a certain amount in the interval [0.8,
1.2], which results in greater convergence. In some cases, for simplicity, the w(t) value is equal to
1. The acceleration coefficients C1 and C2 in equation (19), and in essence, control the extent to
which a particle will move in a single repeat. Values for both coefficients are set to 2.
The performance of the PSO algorithm depends on the parameter settings, which include the
weight inertia w(t), acceleration coefficients C1 and C2, the maximum number of repetitions T,
and the initialization of the population. Weight inertia usually decreases uniformly from the
maximum number of repetitions T.
When a particle is moved to a new position, a new solution is found for each object. This solution
is evaluated by a fitness function.
A WSN with a number of nodes is considered as T={τ1,τ2,…,τN} and the number n of potential
position as P={p1,p2,...,pn} to reduce energy consumption during routing time. After the
production of particles, it is necessary to derive the fitness function.
The fitness function is obtained by choosing the minimum number of potential positions with less
energy consumption (Equation (20))
(20)
1
M
MinF
K
=
In equation (20), K is a potential positions and M is a potential point. The cost of point coverage
( iτ ) should be calculated as an equation (21).
(21)
cos
if ( )
and ( )
( ) ,
i
t i
i
k Coverage k
Coverage of Detection Energy
k Coverage otherwise
τ
τ
τ
≥
=
−
From the combination of equations (20) and (21), equation (22) is produced to calculate energy
consumption with respect to sensor coverage.
(22)2 cos
1
1
( )
N
t i
i
MaxF Coverage
N k
τ
=
=
×
Now that the fitness function was produced for coverage, the fitness function for connecting
sensor nodes should also be calculated. For this purpose, equation (23) is used.
(23)
cos
if ( )
( )
( ) ,
i
t i
i
m Coverage s m
Connection s
m Connection s otherwise
≥
=
−
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In equation (23), ( )iConnection s is the set of sensor nodes within the is range.
In order to calculate the fitness function for calculating energy consumption with respect to
sensor connection, equation (24) is used.
(24)
cost
1
3
( )
M
i
i
Connection s
MaxF
M N
=
=
×
In this paper, for creation of multi-objective fitness function, the sum of weights method is used.
The method of sum of weights is a classical method for solving multi-objective optimization
problems. In this approach, weight Wi is multiplied by any of the targets. Finally, all of the
multiplied quantities are grouped together to convert multiple targets into a scalar target function.
This action generates a general fitness function as equation (25).
(25)1 1 2 2 3 3(1 )totalFitness W F W F W F= × − + × + ×
Optimization of equation (25) leads to improved energy aware routing in the multipath AOMDV
protocol, and can be used efficiently in WSN by using the information gathered from the cluster
head during energy aware routing.
4. SIMULATION
In this paper, simulation will carry out in the MATLAB 2017b environment. In the proposed
method, fuzzy logic is used to fuzzy the LEACH and AOMDV protocols. The fuzzy inference
process includes membership functions, fuzzy operators, and if-then rules. The type of fuzzy
inference system used in this paper is Mamdani. In this method, the fuzzy membership functions
must be non-fuzzy. This will increase the efficiency of non-fuzzy. Figure 8 shows the parameters
of the fuzzy system in the MATLAB environment.
Figure 8. Fuzzy Inference System Parameters
As shown in figure 8, the fuzzy inference system has 4 inputs, 22 rules, and 1 output. The inputs
and outputs of the fuzzy system are indicated in figure 9.
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A total of fuzzy rules between these inputs and the linguistic variables are 22 rules that can
improve clustering and routing [9]. Figure 10 illustrates the fuzzy rules between membership
functions.
The fuzzy rules are based on “and” that the combination of four input variables along with 22
combinational rules between them leads to a level of probability. In figure 11, inputs (hops) in the
x-axis and routing energy in the y-axis with the output of the probability in the z-axis are shown.
According to figure 11, the high blue colored sections in the environment have the highest energy
consumption during cluster-based routing and cluster head selection. Whatever moves upwards,
the green or yellow color will result in the best possible fuzzy output, indicating the best rules and
the combination of input variables in that section.
The probability of selecting a node as a cluster head depends on the inputs and classification.
After obtaining which node is selected as a cluster head in the network, the non-fuzzy operator
will be used. In non-fuzzy, the exact value of a fuzzy number is obtained. Therefore, the definite
number is introduced as the representation of the fuzzy number
There is a variety of methods for non-fuzzy, in which the center of gravity of the fuzzy number is
used in this paper. In other words, the point that has the degree of belonging to maximum is
considered as the gravity center of that fuzzy number.
Figure 9. a) Membership functions and input linguistic variables of the clustering energy, b) membership
functions and input linguistic variables of centrality, c) membership functions and input linguistic variables
of the routing energy, d) membership functions and input linguistic variables of hops, e) membership
functions and output linguistic variables of probability
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Figure 10. Fuzzy rule set
Figure 11. Presentation of a level of fuzzy sets
The output of the fuzzy part causes the cluster head to be selected. The WSN parameters used in
this paper are shown in Table 1.
Table 1. WSN Parameters.
ValueParameter
100Number of nodes in the network
400×400m2
Network dimensions
0.5 JouleInitial energy
IEEE 802.11MAC
433 MHzRadio Frequency
1 m2
Radio range
100 mCommunication coverage
At first, nodes are randomly deployed in the network environment. The difference between the
network length and the actual position of the sensor node in the network for random deployment,
determines the power of the nodes at start time, as determined by equation (26).
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(26)Network length × The actual position of the sensor node < 0.5
Then, cluster headers are selected by fuzzy logic according to membership functions and fuzzy
rules. Figure 12 shows the output of the node deployment section, which is used in the first step
of the 100 round for training and cluster heads are shown in black color in the figure.
Figure 12. Deployment of the node in the first round along with the two cluster heads with black color
Typically, the number of cluster heads can be increased up to 5. To obtain the distance between
the clusters in a network environment and also the closest node to another node in a cluster, the
Euclidean distance in the m-dimensional space is used, as shown in equation (27).
(27)( )
2
1
m
ij ik jk
k
d x x
=
= −
At continuation, the PSO algorithm will be used which will be able to find the optimal path and
can maximize the amount of mathematical expectation for all states in the clusters. After fuzzy
logic clustering operations, routing optimization operations are performed to reduce energy
consumption. Figure 13 shows the current status of routing with the AOMDV protocol in normal
mode and the selection of clusters head with fuzzy logic.
Figure 13. The status of routing with the AOMDV and Fuzzy Logic methods
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During the selection of the cluster head, the AOMDV-based routing operation is also running and
energy consume. The network continues to operate until the end of its energy consumption. The
probability of selecting an optimal node for a cluster head is 0.5.
Finally, the deployment output and cluster heads of figure 12 will be as in figure 14 with minor
variations in each round of training due to the deployment of the initial node in the environment
as well as space change.
Figure 14. Deployment of nodes in the last round
As shown in figure 14, there are several cluster head nodes, and the nodes, due to their overlap,
are nodes that are more energy-consuming in the environment, which, of course, are outside the
cluster. In this paper, three values for the size of the packet to be transmitted in the network are
defined in bits of different sizes, in order to determine the energy consumption versus distance in
the WSN.
The first packet size is 10 bits. Then the PSO algorithm is used to reduce energy consumption in
the AOMDV protocol, which the result of using the PSO algorithm is shown in figure 15.
In the upper part of figure 15, the cluster heads are optimized by the PSO algorithm, and nodes
that have high energy consumption are identified that the reduction of energy consumption during
routing takes into account these nodes.
The lower part of figure 15 shows the energy consumption by using the PSO algorithm that the
PSO algorithm repeatedly reduces energy consumption, and the optimization rate is applied.
Clearly, as a new packet is sent, the energy consumption of the network will rise to a certain
extent but will not be as high as the initial energy consumption, as the paths predefined by the
proposed algorithm are mostly optimal and for the new packages only just make some
adjustments to the previous path.
Now that the energy consumption is optimized, the packets enter the network to get the result. In
figure 16(a), shows energy consumption versus distance with packet size10-bit on the network. A
packet with a length of 12 bits is shown in figure 16(b), and a packet length of 16 bits is shown in
figure 16(c).
Figure 16 results that with increasing data values from 10 to 16 bits at a given distance, the
growth rate of energy consumption is reduced. The reason for this is the use of clustering based
on the proposed method, which has an effective result on the WSN to reduce energy
consumption. Figure 17 shows the current status of the routing with the AOMDV protocol at
working time and improvement of AOMDV with the PSO algorithm.
16. International Journal of Computer Networks & Communications (IJCNC) Vol.10, No.6, November 2018
112
Figure 15. The result of PSO algorithm for optimization
Figure 16. a) The result of energy consumption versus distance of 10 bits, b) The result of energy
consumption versus distance of 12 bits, c) The result of energy consumption versus distance of 16 bits
17. International Journal of Computer Networks & Communications (IJCNC) Vol.10, No.6, November 2018
113
Figure 17. Routing based on AOMDV and its improvement with PSO algorithm
5. CONCLUSIONS
Increasing the efficiency of WSNs is measured and evaluated with a series of parameters. One of
these parameters is the network lifetime that is very important because the nodes in the WSN
have battery limits. Hence, increasing the life of the network in terms of energy consumption in
different situations is important.
Another important parameter is the routing that consumes energy. A methodology that can make
energy aware routing and increase network efficiency is an effective way. Therefore, providing a
method that can address these parameters can be used as an effective method in the WSN.
This paper uses smart methods to reduce energy consumption during routing. The proposed
approach is that uses AOMDV routing protocol and the LEACH clustering protocol. In the
clustering and cluster selection method due to the uncertainty that exists in the LEACH method,
in this paper fuzzy logic including membership functions and fuzzy rules are used. The PSO
algorithm, by optimizing the AOMDV multipath routing protocol with regard to energy
consumption, has shown that the proposed method is an effective and efficient technique and can
reduce 5% energy consumption in WSN compared to AOMDV method.
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AUTHOR
Gholamreza Farahani received his BSc degree in electrical engineering from Sharif
University of Technology, Tehran, Iran, in 1998 and MSc and PhD degrees in electrical
engineering from Amirkabir University of Technology (Polytechnic), Tehran, Iran in
2000 and 2006 respectively. Currently, he is an assistant professor in the Institute of
Electrical and Information Technology, Iranian Research Organization for Science and
Technology (IROST), Iran. His research interest is computer networks especially
routing.