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.
Ameliorate the performance using soft computing approaches in wireless networksIJECEIAES
Wireless sensor networks are an innovative and rapidly advanced network occupying the broad spectrum of wireless networks. It works on the principle of “use with less expense, effort and with more comfort.” In these networks, routing provides efficient and effective data transmission between different sources to access points using the clustering technique. This work addresses the low-energy adaptive clustering hierarchy (LEACH) protocol’s main backdrop of choosing head nodes based on a random value. In this, the soft computing methods are used, namely the fuzzy approach, to overcome this barrier in LEACH. Our approach’s primary goal is to extend the network lifetime with efficient energy consumption and by choosing the appropriate head node in each cluster based on the fuzzy parameters. The proposed clustering algorithm focused on two fuzzy inference structures, namely Mamdani and Sugeno fuzzy logic models in two scenarios, respectively. We compared our approach with four existing works, the conventional LEACH, LEACH using the fuzzy method, multicriteria cluster head delegation, and fuzzy-based energy efficient clustering approach (FEECA) in wireless sensor network. The proposed scenario based fuzzy LEACH protocol approaches are better than the four existing methods regarding stability, network survivability, and energy consumption.
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Net...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.
DESIGNING AN ENERGY EFFICIENT CLUSTERING IN HETEROGENEOUS WIRELESS SENSOR NET...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical
issue that degrades the network performance. Recharging and providing security to the sensor devices is
very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an
important and suitable approach to increase energy efficiency and transmitting secured data which in turn
enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC)
works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the
rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the
network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on
the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all
the cluster heads are formed at a time and selected on rotation based on considering the highest energy of
the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum
flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access
(CSMA), a contention window based protocol is used at the MAC layer for collision detection and to
provide channel access prioritization to HWSN of different traffic classes with reduction in End to End
delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the
cluster head for transmission without depleting the energy. Simulation parameters of the proposed system
such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing
system.
EEIT2-F: energy-efficient aware IT2-fuzzy based clustering protocol in wirel...IJECEIAES
Improving the network lifetime is still a vital challenge because most wireless sensor networks (WSNs) run in an unreached environment and offer almost impossible human access and tracking. Clustering is one of the most effective methods for ensuring that the relevant device process takes place to improve network scalability, decrease energy consumption and maintain an extended network lifetime. Many researches have been developed on the numerous effective clustering algorithms to address this problem. Such algorithms almost dominate on the cluster head (CH) selection and cluster formation; using the intelligent type1 fuzzy-logic (T1-FL) scheme. In this paper, we suggest an interval type2 FL (IT2-FL) methodology that assumes uncertain levels of a decision to be more efficient than the T1-FL model. It is the so-called energy-efficient interval type2 fuzzy (EEIT2-F) low energy adaptive clustering hierarchical (LEACH) protocol. The IT2-FL system depends on three inputs of the residual energy of each node, the node distance from the base station (sink node), and the centrality of each node. Accordingly, the simulation results show that the suggested clustering protocol outperforms the other existing proposals in terms of energy consumption and network lifetime.
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
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.
Ameliorate the performance using soft computing approaches in wireless networksIJECEIAES
Wireless sensor networks are an innovative and rapidly advanced network occupying the broad spectrum of wireless networks. It works on the principle of “use with less expense, effort and with more comfort.” In these networks, routing provides efficient and effective data transmission between different sources to access points using the clustering technique. This work addresses the low-energy adaptive clustering hierarchy (LEACH) protocol’s main backdrop of choosing head nodes based on a random value. In this, the soft computing methods are used, namely the fuzzy approach, to overcome this barrier in LEACH. Our approach’s primary goal is to extend the network lifetime with efficient energy consumption and by choosing the appropriate head node in each cluster based on the fuzzy parameters. The proposed clustering algorithm focused on two fuzzy inference structures, namely Mamdani and Sugeno fuzzy logic models in two scenarios, respectively. We compared our approach with four existing works, the conventional LEACH, LEACH using the fuzzy method, multicriteria cluster head delegation, and fuzzy-based energy efficient clustering approach (FEECA) in wireless sensor network. The proposed scenario based fuzzy LEACH protocol approaches are better than the four existing methods regarding stability, network survivability, and energy consumption.
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Net...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.
DESIGNING AN ENERGY EFFICIENT CLUSTERING IN HETEROGENEOUS WIRELESS SENSOR NET...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical
issue that degrades the network performance. Recharging and providing security to the sensor devices is
very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an
important and suitable approach to increase energy efficiency and transmitting secured data which in turn
enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC)
works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the
rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the
network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on
the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all
the cluster heads are formed at a time and selected on rotation based on considering the highest energy of
the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum
flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access
(CSMA), a contention window based protocol is used at the MAC layer for collision detection and to
provide channel access prioritization to HWSN of different traffic classes with reduction in End to End
delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the
cluster head for transmission without depleting the energy. Simulation parameters of the proposed system
such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing
system.
EEIT2-F: energy-efficient aware IT2-fuzzy based clustering protocol in wirel...IJECEIAES
Improving the network lifetime is still a vital challenge because most wireless sensor networks (WSNs) run in an unreached environment and offer almost impossible human access and tracking. Clustering is one of the most effective methods for ensuring that the relevant device process takes place to improve network scalability, decrease energy consumption and maintain an extended network lifetime. Many researches have been developed on the numerous effective clustering algorithms to address this problem. Such algorithms almost dominate on the cluster head (CH) selection and cluster formation; using the intelligent type1 fuzzy-logic (T1-FL) scheme. In this paper, we suggest an interval type2 FL (IT2-FL) methodology that assumes uncertain levels of a decision to be more efficient than the T1-FL model. It is the so-called energy-efficient interval type2 fuzzy (EEIT2-F) low energy adaptive clustering hierarchical (LEACH) protocol. The IT2-FL system depends on three inputs of the residual energy of each node, the node distance from the base station (sink node), and the centrality of each node. Accordingly, the simulation results show that the suggested clustering protocol outperforms the other existing proposals in terms of energy consumption and network lifetime.
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
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.
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.
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.
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.
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.
MODELING, IMPLEMENTATION AND PERFORMANCE ANALYSIS OF MOBILITY LOAD BALANCING ...IJCNCJournal
We propose in this paper a simulation implementation of Self-Organizing Networks (SON) optimization
related to mobility load balancing (MLB) for LTE systems using ns-3 [1]. The implementation is achieved
toward two MLB algorithms dynamically adjusting handover (HO) parameters based on the Reference
Signal Received Power (RSRP) measurements. Such adjustments are done with respect to loads of both an
overloaded cell and its cells’ neighbours having enough available resources enabling to achieve load
balancing. Numerical investigations through selected key performance indicators (KPIs) of the proposed
MLB algorithms when compared with another HO algorithm (already implemented in ns-3) based on A3
event [2] highlight the significant MLB gains provided in terms global network throughput, packet loss rate
and the number of successful HO without incurring significant overhead.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
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
WIRELESS SENSOR NETWORK CLUSTERING USING PARTICLES SWARM OPTIMIZATION FOR RED...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.
CBHRP: A Cluster Based Routing Protocol for Wireless Sensor NetworkCSEIJJournal
A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol
(CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster
head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to
collect information from target field. On rotation basis, a head-set member receives data from the neighbor
nodes and transmits the aggregated results to the distance base station. This protocol reduces energy
consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP
performs better than other well accepted hierarchical routing protocols like LEACH in term of energy
consumption and time requirement.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
EFFICIENT APPROACH FOR DESIGNING A PROTOCOL FOR IMPROVING THE CAPACITY OF ADH...IJCI JOURNAL
In Adhoc Network, prime issues which affects the deployment, design and performance of an Adhoc
Wireless System are Routing, MAC Scheme, TCP, Multicasting, Energy management, Pricing Scheme &
self-organization, Security & Deployment consideration. Routing protocols are designed in such a way that
it should have improvement of throughput and minimum loss of packets. Another aspect is efficient
management of energy and the requirement of protracted connectivity of the network. The routing
algorithm designed for this network should monitor the energy of the node and route the packet
accordingly. Adhoc Network in general has many limitations such as bandwidth, memory and
computational power. In Adhoc Network there are frequent path break due to mobility. Also time
synchronization is difficult & consumes more Bandwidth. Bandwidth reservations requires complex
Medium Access Control protocol. In this field the work of quantitative and qualitative metrics analysis has
been done. The analysis of protocol performance for improving the capacity of adhoc network using
probabilistic approaches of the network is yet to be proposed. Our probabilistic approach will cover
analysis of various computational parameters for different mobility structures. In our proposed method we
have distributed mobile nodes using Pareto distribution & formulated various energy models using
regression statistic.
In this paper, we propose a new traffic flow model of the Long Term Evaluation (LTE) network for the Evolved Universal Terrestrial Radio Access Network (E-UTRAN). Here only one Evolve Node B (eNB) nearest to the Mobility Management Entity (MME) and Serving Gateway (S-GW) will use the S1 link to bridge the E-UTRAN and Evolved Packet Core (EPC). All the eNBs of a tracking area will be connected to each other by the X2 link. Determination of capacity of a links of such a network is a challenging job since each node offers its own traffic and at the same time conveys traffic of other nodes. In this paper, we apply maximum flow algorithm including superposition theorem to solve the traffic flow of radio network. Using the total flow per subcarrier, a new traffic model is also developed in the paper. The relation among the traffic parameters: ‘blocking probability’, ‘offered traffic’, ‘instantaneous capacity’, ‘average holding time’, and ‘number of users’ are shown graphically under both QPSK and 16-QAM. The concept of the network will be helpful to improve the SINR of the received signal ofeNBslocated long distance relative to MME/S-GW.
PERFORMANCE EVALUATION OF LTE NETWORK USING MAXIMUM FLOW ALGORITHMijcsit
In this paper, we propose a new traffic flow model of the Long Term Evaluation (LTE) network for the Evolved Universal Terrestrial Radio Access Network (E-UTRAN). Here only one Evolve Node B (eNB) nearest to the Mobility Management Entity (MME) and Serving Gateway (S-GW) will use the S1 link to
bridge the E-UTRAN and Evolved Packet Core (EPC). All the eNBs of a tracking area will be connected to each other by the X2 link. Determination of capacity of a links of such a network is a challenging job since each node offers its own traffic and at the same time conveys traffic of other nodes. In this paper, we apply maximum flow algorithm including superposition theorem to solve the traffic flow of radio network. Using the total flow per subcarrier, a new traffic model is also developed in the paper. The relation among the traffic parameters: ‘blocking probability’, ‘offered traffic’, ‘instantaneous capacity’, ‘average holding
time’, and ‘number of users’ are shown graphically under both QPSK and 16-QAM. The concept of the network will be helpful to improve the SINR of the received signal ofeNBslocated long distance relative to MME/S-GW.
AN OPTIMIZED WEIGHT BASED CLUSTERING ALGORITHM IN HETEROGENEOUS WIRELESS SENS...cscpconf
The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in various fields like disastermanagementbattle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH) of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but
some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
A new method for controlling and maintainingIJCNCJournal
Topology Control is an essential technique in a wireless sensor network to extend the operational time of
the sensor nodes. The goal of this technique is to maintain network connectivity and optimize performance
metrics such as network lifetime and throughput. In this paper we presented a new method for controlling
and maintaining topology in wireless sensor networks that show some improvement over the state of art
methods. The results are analyzed based on objective criteria.
Cds based energy efficient topology control algorithm in wireless sensor net...eSAT Journals
Abstract Wireless Sensor Networks (WSNs) are a self organized network which consists of large number of sensor nodes that collects the data in a various environment [1, 2]. The sensors work on battery that have limited lifetime so it is a challenge to create an energy efficient network that can reduce the energy consumption and interference in the network graph and thereby extend the network lifetime [2]. For saving energy and extending network lifetime the topology is a well-known technique in WSNs and the widely used topology control strategy is the construction of Connected Dominating Set (CDS) [3, 4]. In this paper, we construct a CDS based energy efficient topology control algorithm i.e. GCDSTC for WSNs. The performance analysis includes the study of GCDSTC algorithm in terms of complexity and compares it with EBTC (Energy Balanced Topology Control) algorithm. The simulation results indicate that the GCDSTC algorithm reduce the energy consumption and interference in the network graph, in order to enhance the network lifetime. Keywords: Wireless Sensor Network (WSN), Connected Dominating Set (CDS), Topology Control (TC), etc.
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.
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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.
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.
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.
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.
MODELING, IMPLEMENTATION AND PERFORMANCE ANALYSIS OF MOBILITY LOAD BALANCING ...IJCNCJournal
We propose in this paper a simulation implementation of Self-Organizing Networks (SON) optimization
related to mobility load balancing (MLB) for LTE systems using ns-3 [1]. The implementation is achieved
toward two MLB algorithms dynamically adjusting handover (HO) parameters based on the Reference
Signal Received Power (RSRP) measurements. Such adjustments are done with respect to loads of both an
overloaded cell and its cells’ neighbours having enough available resources enabling to achieve load
balancing. Numerical investigations through selected key performance indicators (KPIs) of the proposed
MLB algorithms when compared with another HO algorithm (already implemented in ns-3) based on A3
event [2] highlight the significant MLB gains provided in terms global network throughput, packet loss rate
and the number of successful HO without incurring significant overhead.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
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
WIRELESS SENSOR NETWORK CLUSTERING USING PARTICLES SWARM OPTIMIZATION FOR RED...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.
CBHRP: A Cluster Based Routing Protocol for Wireless Sensor NetworkCSEIJJournal
A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol
(CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster
head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to
collect information from target field. On rotation basis, a head-set member receives data from the neighbor
nodes and transmits the aggregated results to the distance base station. This protocol reduces energy
consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP
performs better than other well accepted hierarchical routing protocols like LEACH in term of energy
consumption and time requirement.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
EFFICIENT APPROACH FOR DESIGNING A PROTOCOL FOR IMPROVING THE CAPACITY OF ADH...IJCI JOURNAL
In Adhoc Network, prime issues which affects the deployment, design and performance of an Adhoc
Wireless System are Routing, MAC Scheme, TCP, Multicasting, Energy management, Pricing Scheme &
self-organization, Security & Deployment consideration. Routing protocols are designed in such a way that
it should have improvement of throughput and minimum loss of packets. Another aspect is efficient
management of energy and the requirement of protracted connectivity of the network. The routing
algorithm designed for this network should monitor the energy of the node and route the packet
accordingly. Adhoc Network in general has many limitations such as bandwidth, memory and
computational power. In Adhoc Network there are frequent path break due to mobility. Also time
synchronization is difficult & consumes more Bandwidth. Bandwidth reservations requires complex
Medium Access Control protocol. In this field the work of quantitative and qualitative metrics analysis has
been done. The analysis of protocol performance for improving the capacity of adhoc network using
probabilistic approaches of the network is yet to be proposed. Our probabilistic approach will cover
analysis of various computational parameters for different mobility structures. In our proposed method we
have distributed mobile nodes using Pareto distribution & formulated various energy models using
regression statistic.
In this paper, we propose a new traffic flow model of the Long Term Evaluation (LTE) network for the Evolved Universal Terrestrial Radio Access Network (E-UTRAN). Here only one Evolve Node B (eNB) nearest to the Mobility Management Entity (MME) and Serving Gateway (S-GW) will use the S1 link to bridge the E-UTRAN and Evolved Packet Core (EPC). All the eNBs of a tracking area will be connected to each other by the X2 link. Determination of capacity of a links of such a network is a challenging job since each node offers its own traffic and at the same time conveys traffic of other nodes. In this paper, we apply maximum flow algorithm including superposition theorem to solve the traffic flow of radio network. Using the total flow per subcarrier, a new traffic model is also developed in the paper. The relation among the traffic parameters: ‘blocking probability’, ‘offered traffic’, ‘instantaneous capacity’, ‘average holding time’, and ‘number of users’ are shown graphically under both QPSK and 16-QAM. The concept of the network will be helpful to improve the SINR of the received signal ofeNBslocated long distance relative to MME/S-GW.
PERFORMANCE EVALUATION OF LTE NETWORK USING MAXIMUM FLOW ALGORITHMijcsit
In this paper, we propose a new traffic flow model of the Long Term Evaluation (LTE) network for the Evolved Universal Terrestrial Radio Access Network (E-UTRAN). Here only one Evolve Node B (eNB) nearest to the Mobility Management Entity (MME) and Serving Gateway (S-GW) will use the S1 link to
bridge the E-UTRAN and Evolved Packet Core (EPC). All the eNBs of a tracking area will be connected to each other by the X2 link. Determination of capacity of a links of such a network is a challenging job since each node offers its own traffic and at the same time conveys traffic of other nodes. In this paper, we apply maximum flow algorithm including superposition theorem to solve the traffic flow of radio network. Using the total flow per subcarrier, a new traffic model is also developed in the paper. The relation among the traffic parameters: ‘blocking probability’, ‘offered traffic’, ‘instantaneous capacity’, ‘average holding
time’, and ‘number of users’ are shown graphically under both QPSK and 16-QAM. The concept of the network will be helpful to improve the SINR of the received signal ofeNBslocated long distance relative to MME/S-GW.
AN OPTIMIZED WEIGHT BASED CLUSTERING ALGORITHM IN HETEROGENEOUS WIRELESS SENS...cscpconf
The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in various fields like disastermanagementbattle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH) of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but
some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
A new method for controlling and maintainingIJCNCJournal
Topology Control is an essential technique in a wireless sensor network to extend the operational time of
the sensor nodes. The goal of this technique is to maintain network connectivity and optimize performance
metrics such as network lifetime and throughput. In this paper we presented a new method for controlling
and maintaining topology in wireless sensor networks that show some improvement over the state of art
methods. The results are analyzed based on objective criteria.
Cds based energy efficient topology control algorithm in wireless sensor net...eSAT Journals
Abstract Wireless Sensor Networks (WSNs) are a self organized network which consists of large number of sensor nodes that collects the data in a various environment [1, 2]. The sensors work on battery that have limited lifetime so it is a challenge to create an energy efficient network that can reduce the energy consumption and interference in the network graph and thereby extend the network lifetime [2]. For saving energy and extending network lifetime the topology is a well-known technique in WSNs and the widely used topology control strategy is the construction of Connected Dominating Set (CDS) [3, 4]. In this paper, we construct a CDS based energy efficient topology control algorithm i.e. GCDSTC for WSNs. The performance analysis includes the study of GCDSTC algorithm in terms of complexity and compares it with EBTC (Energy Balanced Topology Control) algorithm. The simulation results indicate that the GCDSTC algorithm reduce the energy consumption and interference in the network graph, in order to enhance the network lifetime. Keywords: Wireless Sensor Network (WSN), Connected Dominating Set (CDS), Topology Control (TC), etc.
Similar to A Topology Control Algorithm Taking into Account Energy and Quality of Transmission for Software-Defined Wireless Sensor Network (20)
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.
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.
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A Topology Control Algorithm Taking into Account Energy and Quality of Transmission for Software-Defined Wireless Sensor Network
1. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
DOI: 10.5121/ijcnc.2024.16207 107
A TOPOLOGY CONTROL ALGORITHM TAKING INTO
ACCOUNT ENERGY AND QUALITY OF
TRANSMISSION FOR SOFTWARE-DEFINED
WIRELESS SENSOR NETWORK
Hong Thi Chu Hai1
, Le Huu Binh2
and Le Duc Huy3
1
Faculty of Management Information System, Banking Academy of Vietnam,
Hanoi, Vietnam
2
Faculty of Information Technology, University of Sciences, Hue University, Vietnam
3
Faculty of Information Technology, Ha Noi University of Business and
Technology, Vietnam
ABSTRACT
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 Max Power algorithm in terms of average node degree and energy
expansion ratio.
KEYWORDS
SDWN, topology control, genetic algorithm, nonlinear programming.
1. INTRODUCTION
Wireless Sensor Networks (WSNs) are increasingly being used in a variety of fields, particularly
during this period of rapid growth in internet of things applications. The WSNs can be controlled
in three ways: centralized control, decentralized control, and distributed control [1]. The
centralized control model includes a node in the network that stores global information. This
node controls the data transmission from sensor nodes to the base station (BS). The decentralized
control model divides all sensor nodes into clusters, with one node acting as the cluster leader in
each. Data is sent from sensor nodes to the BS via the cluster head node. For the distributed
control model, the sensor nodes play the same role. Control functions are distributed among the
nodes.
To boost the performance of WSNs, some published research has examined architectures,
models, as well as control protocols in the network, where topology control algorithms are an
interesting topic, attracting many research groups recently [2]-[9], [19]. For this topic, the authors
of [6] have proposed an energy efficient topology control algorithm namely RL-CRC
(Reinforcement Learning-based Communication Range Control). The RL-CRC algorithm uses
2. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
108
reinforcement learning to adaptively adjust the communication range of each node in WSN. To
do this, the authors have proposed a reward function that includes two metrics, the node degree
and the communication range. This reward function is used for nodes to tune its communication
range to obtain the optimal topology. According to the simulation results, RL-CRC consumes
much less energy than traditional methods while retaining about the same average
communication range and node degree. In [7], the authors have proposed a topology control
algorithm for ad-hoc networks namely LTRT (Local Tree-based Reliable Topology). It has been
demonstrated theoretically that the LTRT algorithm ensures k-edge connection while maintaining
the properties of the local minimal spanning tree. The efficiency of LTRT and its superiority over
other localized algorithms have been demonstrated by simulation results. In [8], a topology
control algorithm named FLSS (Fault-tolerant Local Spanning Sub-graph) has been proposed for
wireless ad-hoc networks. The FLSS algorithm minimizes the maximum transmission power
used in the network. According to simulation results, FLSS not only has better power efficiency
than existing fault-tolerant topology control algorithms, but it also leads to higher network
capacity. Topology control using fuzzy logic was also implemented in [9]. In this work, a novel
Fuzzy logic-based Topology Control (FTC) algorithm is proposed with the main objective is to
improve the network connectivity. The method of the FTC algorithm is to adaptively change
communication range in order to achieve any desired average node degree. The performance of
algorithm FTC is compared with other well-known algorithms by simulation method.
Recently, the SDN-based centralized control model has been applied to the WSNs [1], [10], [11].
depicts the basic principle of this model. The sensor nodes are either directly or indirectly
connected to the SDN controller via the open- flow protocol. Control functions in the network,
such as routing, signaling, topology control, and so on, are concentrated at the SDN controller.
The SDWSN model has been used to improve control protocols in the WSN network, most
notably routing protocols [12], [13], topology control [14], [15], and clustering protocol [16],
[17]. For the topic of topology control using SDN, the authors in [15] proposed a
Figure 1. An example of software-defined wireless sensor networks (SDWSN)
decentralized topology control algorithm with the goal of improving the efficiency of energy use.
The algorithm is named EEHTC (Energy-Efficient Hierarchical Topology Control) dividing the
control into two layers. One is to control the topology in the lower layer with conventional sensor
nodes. The second is to control the topology in the upper layer for software control sensor nodes.
When comparing with other algorithms, the EEHTC algorithm increases the existence time of
3. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
109
nodes and reduces energy consumption. In [18], the authors have proposed a SDN-based
manageable topology formation for flying ad hoc networks (FANET) to reduce the mobility
negative effects of UAVs on the communication and improve the network performance.
Simulation results have shown that the proposed solution gives high efficiency in terms of packet
loss within the required delay limit.
We discovered from the published research projects that topology control is a successful method
for enhancing network performance, particularly in terms of enhancing energy efficiency. There
are many various ways to implement topology control algorithms, however adopting SDWSN as
one of them provides numerous benefits. This is due to the algorithm being run at the SDN
controller in accordance with the centralized control principle, which makes it easy to optimize
performance metrics. In this paper, we suggest a new topology control algorithm for SDWSNs.
Using a nonlinear programming (NP) problem, we develop the topology control algorithm with
the objective of optimizing the maximal communication range and desired degree. At the
SDWSN controller, this NP problem is resolved by using the genetic algorithm (GA) to select the
optimal topology.
The next sections of this paper are organized as follows. Section 3 presents our proposed routing
algorithm. Some simulation results and discussion are presented in section 3. Finally, concluding
remarks and promising future study items are given in Section 4.
2. OUR PROPOSED ALGORITHM
2.1. Concepts and Metrics
In this section, we express the concepts and metrics that will be used for the objective function
and the constraints in our proposed algorithm in the next sub-section.
2.1.1.Connected Node
A sensor node I is referred to as the connected node if and only if there is at least one route from
it to BS. Returning to the example as shown in node 8 is not a connected node because there is no
route from it to BS. The connected node is represented by all the remaining nodes.
2.1.2.Desired- Proximity Degree Node
A Desired-proximity degree node is defined as a node whose degree is within the range [k-,
k+], where k is the desired degree and is a given positive integer. Let i be a variable
indicating whether node I is a k-proximity degree node or not, return 1 if it is true and 0
otherwise. Then i is determined by
otherwise
k
k
if i
i
0
1
(1)
where i is the degree of the node I, defined as the number of its neighbours.
2.2. Our Proposed Algorithm
In this section, we present the SDN-based QoT and Energy efficient Topology Control (SQETC)
algorithm, proposed for SDWSNs. The main goal of the SQETC algorithm is to create a topology
4. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
110
that maximizes energy efficiency at nodes while also providing the best QoT in the network. In
an SDWSN topology, the degree of the nodes has the greatest influence on the energy
consumption. We, therefore, use the metric i as defined in (1) to optimize energy use. In
addition, the communication range of each node is used to optimize the QoT in the network.
Thence we define a fitness function as follows:
max
..
1
1 )
(
)
1
(
r
r
Max
n
n
F i
n
i
n
i i
(2)
where is a floating parameter in the range [0, 1] which is used to control the importance of
metrics. The SQETC algorithm can be formulated as a nonlinear programming (NP) problem as
follows:
F
Minimize (3)
subject to the following constraints:
N
i
r
r
r i
,
max
min (4)
N
i
ci
,
1 (5)
where rmin and rmax are the minimum and maximum communication range of each node,
respectively. Equations (4) is the constraints of the communication range of sensor nodes.
Equations (5) is the constraints of network connectivity, where ci is a variable indicating whether
the node I is the connected node or not, determined by.
otherwise
node
connected
a
is
I
if
ci
0
1
(6)
By solving the NP problem with the objective function (3), the constraints (4) and (5), we find the
solution R = {ri|i = 1 .. N} which is the optimal communication range of nodes so that the
resulting topology has the mean degree of nodes close to the desired degree.
Algorithm 1. The pseudo code of the SQETC algorithm
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
The SDN controller collects information about the location and
communication range of each node through control packets;
Formulate the NP problem according to (3), (4), and (5);
Solve the NP problem in step (2);
for (each node i N)
Adjust the communication range of the node i based on the solution
found in step (3);
endfor;
Create the topology based on adjusted communication ranges of all
nodes;
Algorithm 1 presents the pseudo-code of the SQETC algorithm. Each node sends a control packet
to the SDN controller containing information about its current location and communication range
whenever the topology network needs to be updated. Based on this information, the SDN
controller formulates the NP problem according to (3), (4) ,and (5). This NP problem is solved at
the SDN Controller by an approximate optimization algorithm. In this work, we use a genetic
algorithm (GA) to solve it, which returns the communication range of each node. Based on this
result, the node adjusts its communication range to obtain the optimal topology.
5. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
111
3. PERFORMANCE EVALUATION
3.1. Simulation Scenarios
The performance of the SQETC algorithm was evaluated by simulation method using Matlab
software. We use the GA algorithm in the Matlab optimization tool to solve the NP problem that
is proposed in subsection 2.2. The SQETC algorithm is compared with the network topology case
using maximum power, named MaxPower. The MaxPower is the default case in wireless
networks in general, and WSN in particular. In this case, the nodes always operate with the
widest possible communication area. A wireless connection is formed when two nodes are within
range of each other. The network topology is comprised of all nodes and wireless connections.
Evaluation metrics include average node degree, energy consumption rate, and path loss. Tables
1 and 2 show how the simulation scenarios are configured. Despite the randomness of the GA
optimization algorithm, each scenario is run 50 times to ensure the objectivity of the simulation
results. The findings presented in this paper are based on an average of 50 simulations.
Table 1. Technical parameters of simulation scenarios
Parameters Setting
Network area 1000 × 1000 [m2
]
Maximum communication range 250 [m]
Number of sensor nodes From 40 to 100
Desired degree of each node (k) From 3 to 5
Coefficient 1
Topology control algorithm SQETC, MaxPower
Optimal algorithm for solving NP problem GA
Number of simulation runs per scenario 50
Table 2. GA algorithm parameters used to solve the NP problem of the SQETC algorithm
Parameters Setting
Selection function Stochastic uniform
Crossover function Scattered
Mutation function Adaptive feasible
Population size 50
Max iteration 1000
3.2. Simulation Results
Figure 1 compares the network topology obtained using SQETC and MaxPower algorithms. In
this case, the number of sensor nodes is 40 and the desired degree of each node is 4. We can
observe that, in the case of MaxPower (result in
Figure 1a), the topology consists of many wireless links between nodes. The maximum,
minimum and mean of node degrees are 11, 3 and 6, respectively. This topology is inefficient
because the degree difference between the nodes is quite large, easily leading to bottleneck
congestion at some nodes when data transmission. In addition, because the topology has many
wireless links, the nodes have to spend a lot of energy to maintain the links. For the case of using
SQETC algorithm (results in
Figure 1b), the obtained topology has a balanced degree of nodes. The maximum, minimum and
mean of node degrees are 5, 2 and 3.67, respectively. Thus, the average node degree is very close
to the desired degree (k = 4), this topology is more optimal than the topology of the MaxPower
algorithm.
6. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
112
(a) (b)
Figure 1. SDWSN topology comparison when using algorithms (a) MaxPower and (b) SQETC in case the
number of nodes is 40, desired degree is 4.
(a) (b)
Figure 2. SDWSN topology comparison when using algorithms (a) MaxPower and (b) SQETC in case the
number of nodes is 50, desired degree is 4.
The obtained results are also quite similar for the simulation scenario where the number of sensor
nodes is 50, this is clearly shown in Figure 3. In the case of MaxPower (result in Figure 3a), The
maximum, minium and mean of node degrees are 12, 3 and 7.36, respectively. Thus, the node
degree difference is also very large. In case the SQETC algorithm is used, the resulting topology
has a more balanced node degree and is closer to the desired degree. Specifically, the mean
degree is 3.85. These results have shown that the topology obtained using the SQETC algorithm
is more optimal than in the case of MaxPower.
Next, we examine the average node degree versus the number of nodes. The results are shown in
Figure 4 and Figure 5 for the cases where the desired degree is 4 and 5, respectively. We can
observe that, in the default case (MaxPower), the larger the number of nodes, the higher the
average node degree. This is obvious because when the number of nodes is large, the node
density is thicker. Because the MaxPower algorithm configures the topology using the maximum
communication range, each node will have many neighbors. For the SQETC algorithm, the
average node degree is close to the desired degree even when the number of nodes is large.
Specifically, considering the case of the desired degree of 4, the topology obtained by the SQETC
7. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
113
algorithm has an average degree of 3.71 (Figure 4). In the case of a desired degree of 5, the
average node degree of the topology is 4.82 if the SETC algorithm is used.
Figure 3. Compare average node degree of algorithms SQETC and MaxPower when desired degree is 4
Figure 4. Compare the average node degree of algorithms SQETC and MaxPower when the desired
degree is 5
Since the topology obtained by the SQETC algorithm has an average degree closer to the desired
degree than in the case of MaxPower, the SQETC algorithm provides better energy efficiency.
This is evident in the results obtained in Figures 6 and 7. Energy efficiency is analyzed through
the metric of energy expansion ratio (EER), which is determined by [7]:
[%]
100
max
E
E
EER ave
(7)
where Eave is the average transmission power of all nodes and Emax is the maximum transmission
power to reach the maximum communication range (250 [m] in simulation scenarios).
8. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
114
Figure 5. Compare energy expended ratio of algorithms SQETC and MaxPower when desired degree is 4
Figure 6. Compare energy expended ratio of algorithms SQETC and MaxPower when desired degree is 5
The results obtained in Figure 6 and Figure 7 show that, the EER in the case of using the SQETC
algorithm is much lower than that of the MaxPower algorithm. Considering the case of total
nodes is 50, the EER for the case of MaxPower is 86.64%. Meanwhile, if using the SQETC
algorithm, the EER is only 48.22% and 55.90% respectively for the cases where the desired node
degree is 4 and 5. For the cases where the number of nodes is larger, the EER is lower when the
number of nodes is higher. Thus, the SQETC algorithm brings high energy efficiency, especially
with WSNs where the nodes are highly distributed.
4. CONCLUSIONS
Topology control in SDWSN is a research topic that has attracted the attention of many research
groups recently. An optimized network topology improves network performance. In this paper,
we propose a new topology control algorithm for SDWSNs. Our approach is to model topology
control as an NP problem with the goal to optimizing two metrics: maximum communication
range and desired degree. This NP problem is solved at the SDWSN controller by employing the
GA algorithm. In terms of average node degree and energy efficiency, the simulation results
show that the proposed algorithm outperforms the MaxPower case.
9. International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.2, March 2024
115
Although our proposed algorithm improved SDWSN performance, in the case of rapidly moving
nodes, the network topology must be updated regularly. As a result, the computational
complexity at the SDN controller grows. This is a limitation of the proposed algorithm. We will
continue to research solutions to this problem in the future.
CONFLICTS OF INTEREST
The authors declare no conflict of interest.
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AUTHORS
Hong Thi Hai Chu has over 20 years of teaching experience and has participated in
various IT projects such as Developing a student attendance system using
fingerprint and face recognition, a Course schedule and classroom management
system, anOnline exam organization and management system, Enterprise resource
management system providing clean water on GIS platform, etc. She holds a
Bachelor's degree in Mathematics and Computer Science from the Hanoi National
University of Education, a Master's degree in Information Technology from the
Hanoi University of Engineering and Technology, and a Ph.D in Information
System Management from the National Economics University, Vietnam. In addition to teaching and
participating in projects, she is also the head, editor, and member of many sectoral, and grassroots-level
research projects. Her research focuses on topics such as Next Generation Technology (NGN), Data
management, Data Security, Education systems, Enterprise information systems, and Applications of
geographic information systems in daily life.
Le Huu Binh received his BE degree in Telecommunications and Electronics from Da
Nang University of Technology, Vietnam, his MSc degree in Computer Sciences from
Hue University of Sciences, Vietnam, and his PhD degree in Informatics from
Vietnam Academy of Science and Technology (GUST) in 2001, 2007, and 2020,
respectively. He worked as a senior engineer with the Transmission and Switching
Exchange of the Hue Telecommunications Centre, Thua Thien Hue of the Vietnam
Posts and Telecommunications Group (VNPT) from 2001 to 2009. From 2010 to 2021,
he worked at the Hue Industrial College (HUEIC), Vietnam, where he was the dean of
the Faculty of Information Technology and Telecommunications. Since the beginning of 2022, he has been
with the Faculty of Information Technology, University of Sciences (HUSC), Hue University, Hue City,
Vietnam, where he is now a lecturer. His current research interests are next-generation wireless network
technology, software- defined networking, the application of machine learning, and artificial intelligence in
network technology.
Huy D. Le was born in Bac Ninh province, Vietnam in 1990. He received a B.E. degree
in Information Technology from the Hanoi University of Business and Technology, in
2012 and an M.A. degree in Computer Science from the Thai Nguyen University of
Information And Communication Technology, in 2015. He is currently studying for his
Ph.D. at the Graduate University of Sciences and Technology; Vietnam Academy of
Science and Technology. His research interests include computer network and network
security.