The document proposes an Energy and Distance Aware Multi-Objective Golden Eagle Optimization (ED-MOGEO) algorithm for clustering and routing in wireless sensor networks. It aims to reduce energy consumption and prolong network lifetime. ED-MOGEO uses two fitness functions - Euclidean distance and energy - to select cluster heads and find optimal routes between nodes and the base station. Simulation results show ED-MOGEO achieves better performance than existing methods in terms of residual energy, end-to-end delay, packet delivery ratio, routing overhead, and throughput.
OPTIMIZED CLUSTER ESTABLISHMENT AND CLUSTER-HEAD SELECTION APPROACH IN WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
Optimized Cluster Establishment and Cluster-Head Selection Approach in WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
A CLUSTER-BASED ROUTING PROTOCOL AND FAULT DETECTION FOR WIRELESS SENSOR NETWORKIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be
deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a
consequence, the main goal is to reduce the overall energy consumption using clustering protocols which
have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and
routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend
the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices
and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated
widely and the results are compared with related works. The experimental results show that the proposed
algorithm provides an effective improvement in terms of energy consumption, data accuracy and network
lifetime
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption.
Proposed energy efficient clustering and routing for wireless sensor networkIJECEIAES
Wireless sensor network (WSN) is considered a growing research field that includes numerous sensor nodes used to gather, process, and broadcast information. Energy efficiency is considered one of the challenging tasks in the WSN. The clustering and routing are considered capable approaches to solve the issues of energy efficiency and enhance the network’s lifetime. In this research, the multi-objective-energy based black widow optimization algorithm (M-EBWOA) is proposed to perform the cluster-based routing over the WSN. The M-EBWOA-based optimal cluster head discovery is used to assure an energy-aware routing over the WSN. The main goal of this M-EBWOA is to minimize the energy consumed by the nodes while improving the data delivery of the WSN. The performance of the M-EBWOA is analyzed as alive and dead nodes, dissipated energy, packets sent to base station, and life expectancy. The existing research such as lowenergy adaptive clustering hierarchy (LEACH), hybrid grey wolf optimizerbased sunflower optimization (HGWSFO), genetic algorithm-particle swarm optimization (GA-PSO), and energy-centric multi-objective Salp Swarm algorithm (ECMOSSA) are used to evaluate the efficiency of M-EBWOA. The alive nodes of the M-EBWOA are 100 for 2,500 rounds, which is higher than the LEACH, HGWSFO, GA-PSO, and ECMOSSA.
An energy efficient optimized cluster establishment methodology for sensor n...nooriasukmaningtyas
The compatibility of WSN is with various applications such as; healthcar eand environmental monitoring. Whereas nodes present in that network have limited ‘battery-life’ that cause difficulty to replace and recharge those batteries after deployment. Energy efficiency is a major problem in the present situation. In present, many algorithms based on energy efficiency have been introduced to improvise the conservation of energy in WSN. The LEACH algorithm improvises the network lifetime in comparison to direct transmission and multi-hop, but it has several limitations. The selection of CHs can be randomly done that doesn’t confirm the optimal solution, proper distribution and it lacks during complete network management. The centralized EE optimized cluster establishment approach (OCEA) for sensor nodes is proposed to decrease the average energy dissipation and provide significant improvement. The proposed EE WSN model with the sensor nodes is examined under a real-time scenario and it is compared with stateof-art techniques where it balances the energy consumption of the network and decreasing the cluster head number.
OPTIMIZED CLUSTER ESTABLISHMENT AND CLUSTER-HEAD SELECTION APPROACH IN WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
Optimized Cluster Establishment and Cluster-Head Selection Approach in WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
A CLUSTER-BASED ROUTING PROTOCOL AND FAULT DETECTION FOR WIRELESS SENSOR NETWORKIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be
deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a
consequence, the main goal is to reduce the overall energy consumption using clustering protocols which
have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and
routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend
the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices
and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated
widely and the results are compared with related works. The experimental results show that the proposed
algorithm provides an effective improvement in terms of energy consumption, data accuracy and network
lifetime
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption.
Proposed energy efficient clustering and routing for wireless sensor networkIJECEIAES
Wireless sensor network (WSN) is considered a growing research field that includes numerous sensor nodes used to gather, process, and broadcast information. Energy efficiency is considered one of the challenging tasks in the WSN. The clustering and routing are considered capable approaches to solve the issues of energy efficiency and enhance the network’s lifetime. In this research, the multi-objective-energy based black widow optimization algorithm (M-EBWOA) is proposed to perform the cluster-based routing over the WSN. The M-EBWOA-based optimal cluster head discovery is used to assure an energy-aware routing over the WSN. The main goal of this M-EBWOA is to minimize the energy consumed by the nodes while improving the data delivery of the WSN. The performance of the M-EBWOA is analyzed as alive and dead nodes, dissipated energy, packets sent to base station, and life expectancy. The existing research such as lowenergy adaptive clustering hierarchy (LEACH), hybrid grey wolf optimizerbased sunflower optimization (HGWSFO), genetic algorithm-particle swarm optimization (GA-PSO), and energy-centric multi-objective Salp Swarm algorithm (ECMOSSA) are used to evaluate the efficiency of M-EBWOA. The alive nodes of the M-EBWOA are 100 for 2,500 rounds, which is higher than the LEACH, HGWSFO, GA-PSO, and ECMOSSA.
An energy efficient optimized cluster establishment methodology for sensor n...nooriasukmaningtyas
The compatibility of WSN is with various applications such as; healthcar eand environmental monitoring. Whereas nodes present in that network have limited ‘battery-life’ that cause difficulty to replace and recharge those batteries after deployment. Energy efficiency is a major problem in the present situation. In present, many algorithms based on energy efficiency have been introduced to improvise the conservation of energy in WSN. The LEACH algorithm improvises the network lifetime in comparison to direct transmission and multi-hop, but it has several limitations. The selection of CHs can be randomly done that doesn’t confirm the optimal solution, proper distribution and it lacks during complete network management. The centralized EE optimized cluster establishment approach (OCEA) for sensor nodes is proposed to decrease the average energy dissipation and provide significant improvement. The proposed EE WSN model with the sensor nodes is examined under a real-time scenario and it is compared with stateof-art techniques where it balances the energy consumption of the network and decreasing the cluster head number.
IMPROVEMENT of MULTIPLE ROUTING BASED on FUZZY CLUSTERING and PSO ALGORITHM I...IJCNCJournal
One of the most important issues discussed in Wireless Sensor Networks (WSNs) is how to transfer information from nodes within the network to the base station and select the best possible route for transmission of this information, taking into account energy consumption for the network lifetime with
maximum reliability and security. Hence, it would be useful to provide a suitable method that would have the features mentioned. This paper uses an Ad-hoc On-demand Multipath Distance Vector (AOMDV) as a routing protocol. This protocol has high energy consumption due to its multipath. However, it is a big challenge if it can reduce AOMDV energy consumption. Therefore, clustering operations for nodes are of high priority to determine the head of clusters which LEACH protocol and fuzzy logic and Particle Swarm Optimization (PSO) algorithm are used for this purpose. Simulation results represent 5% improvement in energy consumption in a WSN compared to AOMDV method.
Routing Optimization with Load Balancing: an Energy Efficient ApproachEswar Publications
The area of Wireless Sensor Network (WSN) is covered with considerable range of problems, where majority of research attempts were carried out to enhance the network lifetime of WSN. But very few of the studies have proved successful. This manuscript discusses about a structure for optimizing routing and load balancing that uses standard radio and energy model to perform energy optimization by introducing a novel routing agent. The routing agent is built within aggregator node and base station to perform self motivated reconfiguration in case of energy depletion. Compared with standard LEACH algorithm, the proposed technique has better energy efficiency within optimal data aggregation duration.
Energy efficient data transmission using multiobjective improved remora optim...IJECEIAES
A wireless sensor network (WSN) is a collection of nodes fitted with small sensors and transceiver elements. Energy consumption, data loss, and transmission delays are the major drawback of creating mobile sinks. For instance, battery life and data latency might result in node isolation, which breaks the link between nodes in the network. These issues have been avoided by means of mobile data sinks, which move between nodes with connection issues. Therefore, energy aware multiobjective improved
remora optimization algorithm and multiobjective ant colony optimization
(EA-MIROA-MACO) is proposed in this research to improve the WSN’s energy efficiency by eliminating node isolation issue. MIRO is utilized to pick the optimal cluster heads (CHs), while multiobjective ant colony optimization (MACO) is employed to find the path through the CHs. The EA-MIROA-MACO aims to optimize energy consumption in nodes and enhance data transmission within a WSN. The analysis of EA-MIROA-MACO’s performance is conducted by considering the number of alive along with dead nodes, average residual energy, and network lifespan. The EA-MIROA-MACO is compared with traditional approaches such as mobile sink and fuzzy based relay node routing (MSFBRR) protocol as well as hybrid neural network (HNN). The EA-MIROA-MACO demonstrates a higher number of alive nodes, specifically 192, over the MSFBRR and HNN for 2,000 rounds.
ENERGY-EFFICIENT MULTI-HOP ROUTING WITH UNEQUAL CLUSTERING APPROACH FOR WIREL...IJCNCJournal
The development of an energy-efficient routing protocol, capable of extending the life of the network, is one of the main constraints of wireless sensor networks (WSN). Research studies on WSN routing prove that clustering offers an effective approach to prolong the lifetime of a WSN, particularly when it is combined with multi-hop communication that can reduces energy costs by minimizing the distance between transmitter and receiver. Most clustering algorithms using multi-hop in data transmission encounter the hotspot problem. In this work, an Energy-efficient Multi-hop routing with Unequal Clustering approach (EMUC) is proposed, to create clusters of different sizes, which depend on the distance between the sensor node and the base station. Equilibrate the energy dissipation between the cluster heads is the purpose of this approach by adopting multi-hop communication to relay data to the base station. The implementation of multi-hop mode to transmit data to the base station reduces the energy cost of transmission over long distances. The effectiveness of this approach is validated through performed simulations, which prove that EMUC balances energy consumption between sensor nodes, mitigates the hotspots problem, saves more energy and significantly extends the network lifetime.
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
Energy Aware Talented Clustering with Compressive Sensing (TCCS) for Wireless...IJCNCJournal
Wireless sensor networks (WSNs) are networks of sensor nodes that interact wirelessly to gather information about the surrounding environment. Nodes are often low-powered and dispersed in an ad hoc, decentralized manner. Although WSNs have gained in popularity, they still have several serious shortcomings, like limited battery life and bandwidth. In this paper, the cluster head (CH) selection, the Compressive Sensing (CS) theory, the Connection-based Decentralized Clustering (CDC), the relay node selection, and the Multi Objective Genetic Algorithm (MOGA)are all taken into account The initial stage provided a theoretical revision to the concepts of network construction, compressive sensing, and MOGA, which impacted the improvement of network lifetime. In the second stage developed a novel model such as Energy Aware Talented Clustering with Compressive Sensing (TCCS) for the sensor network. This approach considers increasing longevity but also raises the network's overall quality of service (QoS). In the analysis, the TCCS model is applied to both the centralized and distributed networks and compared with the existing methods. When compared to the previous methods, the simulation results show that the proposed work performs better in terms of the calculation of maximum packet delivery ratio of 93.93 percent, minimum energy consumption of 8.04J, maximum energy efficiency of 91.04 percent, maximum network throughput of 465.51kbps, minimum packet loss of 282 packets, and minimum delay of 63.82 msec.
ENERGY AWARE TALENTED CLUSTERING WITH COMPRESSIVE SENSING (TCCS) FOR WIRELESS...IJCNCJournal
Wireless sensor networks (WSNs) are networks of sensor nodes that interact wirelessly to gather
information about the surrounding environment. Nodes are often low-powered and dispersed in an ad hoc,
decentralized manner. Although WSNs have gained in popularity, they still have several serious
shortcomings, like limited battery life and bandwidth. In this paper, the cluster head (CH) selection, the
Compressive Sensing (CS) theory, the Connection-based Decentralized Clustering (CDC), the relay node
selection, and the Multi Objective Genetic Algorithm (MOGA)are all taken into account The initial stage
provided a theoretical revision to the concepts of network construction, compressive sensing, and MOGA,
which impacted the improvement of network lifetime. In the second stage developed a novel model such as
Energy Aware Talented Clustering with Compressive Sensing (TCCS) for the sensor network. This
approach considers increasing longevity but also raises the network's overall quality of service (QoS). In
the analysis, the TCCS model is applied to both the centralized and distributed networks and compared
with the existing methods. When compared to the previous methods, the simulation results show that the
proposed work performs better in terms of the calculation of maximum packet delivery ratio of 93.93
percent, minimum energy consumption of 8.04J, maximum energy efficiency of 91.04 percent, maximum
network throughput of 465.51kbps, minimum packet loss of 282 packets, and minimum delay of 63.82 msec.
AN EXTENDED K-MEANS CLUSTER HEAD SELECTION ALGORITHM FOR EFFICIENT ENERGY CON...IJNSA Journal
Effective use of sensor nodes’ batteries in wireless sensor networks is critical since the batteries are difficult to recharge or replace. This is closely connected to the networks’ lifespan since once the battery is used up, the node is no longer useful. The entire network will not function if 60 to 80% of the nodes in it have completely depleted their energy. In order to minimize energy usage and sustain the network for a long time, many cluster head selection algorithms have been developed. However, the existing cluster head selection algorithms such as K-Means, particle swarm selection optimization (PSO), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Fuzzy C-Means (FCM) cluster head election algorithm have not fully reduced the issue of energy usage in WSN. The objective of this paper was to develop an extended K Mean Cluster Head selection(CHS) algorithm that uses remaining energy, distance between node and base station, distance between nodes and neighbour nodes, node density, node degree Maximum Cluster size, received signal strength indicator (RSSI) and Signal to Noise Ratio. The algorithm developed was used to enhance the lifespan of WSNs. The performance of the simulated variants of LEACH routing protocols is measured and evaluated using the quantitative research methodology. Utilizing residual node energy, packet delivery ratio, throughput, network longevity, average energy usage, and the number of live and dead node, the suggested approach is contrasted to previous approaches. From the study we observed that the proposed approach outperforms existing actual LEACH, Mod-LEACH and TSILEACH approaches.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
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
Energy efficiency has recently turned out to be primary issue in wireless sensor networks.
Sensor networks are battery powered, therefore become dead after a certain period of time. Thus,
improving the data dissipation in energy efficient way becomes more challenging problem in order to
improve the lifetime for sensor devices. The clustering and tree based data aggregation for sensor
networks can enhance the network lifetime of wireless sensor networks. Non-dominated Sorting Genetic
Algorithm (NSGA) -III based energy efficient clustering and tree based routing protocol is proposed.
Initially, clusters are formed on the basis of remaining energy, then, NSGA-III based data aggregation
will come in action to improve the inter-cluster data aggregation further. Extensive analysis demonstrates
that proposed protocol considerably enhances network lifetime over other techniques.
Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterog...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
SECTOR TREE-BASED CLUSTERING FOR ENERGY EFFICIENT ROUTING PROTOCOL IN HETEROG...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
Hierarchical Coordination for Data Gathering (HCDG) in Wireless Sensor NetworksCSCJournals
A wireless sensor network (WSN) consists of large number of sensor nodes where each node operates by a finite battery for sensing, computing, and performing wireless communication tasks. Energy aware routing and MAC protocols were proposed to prolong the lifetime of WSNs. MAC protocols reduce energy consumption by putting the nodes into sleep mode for a relatively longer period of time; thereby minimizing collisions and idle listening time. On the other hand, efficient energy aware routing is achieved by finding the best path from the sensor nodes to the Base Sta-tion (BS) where energy consumption is minimal. In almost all solutions there is always a tradeoff between power consumption and delay reduction. This paper presents an improved hierarchical coordination for data gathering (HCDG) routing schema for WSNs based on multi-level chains formation with data aggregation. Also, this paper provides an analytical model for energy consumption in WSN to compare the performance of our proposed HCDG schema with the near optimal energy reduction methodology, PEGASIS. Our results demonstrate that the proposed routing schema provides relatively lower energy consumption with minimum delay for large scale WSNs.
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
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IMPROVEMENT of MULTIPLE ROUTING BASED on FUZZY CLUSTERING and PSO ALGORITHM I...IJCNCJournal
One of the most important issues discussed in Wireless Sensor Networks (WSNs) is how to transfer information from nodes within the network to the base station and select the best possible route for transmission of this information, taking into account energy consumption for the network lifetime with
maximum reliability and security. Hence, it would be useful to provide a suitable method that would have the features mentioned. This paper uses an Ad-hoc On-demand Multipath Distance Vector (AOMDV) as a routing protocol. This protocol has high energy consumption due to its multipath. However, it is a big challenge if it can reduce AOMDV energy consumption. Therefore, clustering operations for nodes are of high priority to determine the head of clusters which LEACH protocol and fuzzy logic and Particle Swarm Optimization (PSO) algorithm are used for this purpose. Simulation results represent 5% improvement in energy consumption in a WSN compared to AOMDV method.
Routing Optimization with Load Balancing: an Energy Efficient ApproachEswar Publications
The area of Wireless Sensor Network (WSN) is covered with considerable range of problems, where majority of research attempts were carried out to enhance the network lifetime of WSN. But very few of the studies have proved successful. This manuscript discusses about a structure for optimizing routing and load balancing that uses standard radio and energy model to perform energy optimization by introducing a novel routing agent. The routing agent is built within aggregator node and base station to perform self motivated reconfiguration in case of energy depletion. Compared with standard LEACH algorithm, the proposed technique has better energy efficiency within optimal data aggregation duration.
Energy efficient data transmission using multiobjective improved remora optim...IJECEIAES
A wireless sensor network (WSN) is a collection of nodes fitted with small sensors and transceiver elements. Energy consumption, data loss, and transmission delays are the major drawback of creating mobile sinks. For instance, battery life and data latency might result in node isolation, which breaks the link between nodes in the network. These issues have been avoided by means of mobile data sinks, which move between nodes with connection issues. Therefore, energy aware multiobjective improved
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(EA-MIROA-MACO) is proposed in this research to improve the WSN’s energy efficiency by eliminating node isolation issue. MIRO is utilized to pick the optimal cluster heads (CHs), while multiobjective ant colony optimization (MACO) is employed to find the path through the CHs. The EA-MIROA-MACO aims to optimize energy consumption in nodes and enhance data transmission within a WSN. The analysis of EA-MIROA-MACO’s performance is conducted by considering the number of alive along with dead nodes, average residual energy, and network lifespan. The EA-MIROA-MACO is compared with traditional approaches such as mobile sink and fuzzy based relay node routing (MSFBRR) protocol as well as hybrid neural network (HNN). The EA-MIROA-MACO demonstrates a higher number of alive nodes, specifically 192, over the MSFBRR and HNN for 2,000 rounds.
ENERGY-EFFICIENT MULTI-HOP ROUTING WITH UNEQUAL CLUSTERING APPROACH FOR WIREL...IJCNCJournal
The development of an energy-efficient routing protocol, capable of extending the life of the network, is one of the main constraints of wireless sensor networks (WSN). Research studies on WSN routing prove that clustering offers an effective approach to prolong the lifetime of a WSN, particularly when it is combined with multi-hop communication that can reduces energy costs by minimizing the distance between transmitter and receiver. Most clustering algorithms using multi-hop in data transmission encounter the hotspot problem. In this work, an Energy-efficient Multi-hop routing with Unequal Clustering approach (EMUC) is proposed, to create clusters of different sizes, which depend on the distance between the sensor node and the base station. Equilibrate the energy dissipation between the cluster heads is the purpose of this approach by adopting multi-hop communication to relay data to the base station. The implementation of multi-hop mode to transmit data to the base station reduces the energy cost of transmission over long distances. The effectiveness of this approach is validated through performed simulations, which prove that EMUC balances energy consumption between sensor nodes, mitigates the hotspots problem, saves more energy and significantly extends the network lifetime.
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
Energy Aware Talented Clustering with Compressive Sensing (TCCS) for Wireless...IJCNCJournal
Wireless sensor networks (WSNs) are networks of sensor nodes that interact wirelessly to gather information about the surrounding environment. Nodes are often low-powered and dispersed in an ad hoc, decentralized manner. Although WSNs have gained in popularity, they still have several serious shortcomings, like limited battery life and bandwidth. In this paper, the cluster head (CH) selection, the Compressive Sensing (CS) theory, the Connection-based Decentralized Clustering (CDC), the relay node selection, and the Multi Objective Genetic Algorithm (MOGA)are all taken into account The initial stage provided a theoretical revision to the concepts of network construction, compressive sensing, and MOGA, which impacted the improvement of network lifetime. In the second stage developed a novel model such as Energy Aware Talented Clustering with Compressive Sensing (TCCS) for the sensor network. This approach considers increasing longevity but also raises the network's overall quality of service (QoS). In the analysis, the TCCS model is applied to both the centralized and distributed networks and compared with the existing methods. When compared to the previous methods, the simulation results show that the proposed work performs better in terms of the calculation of maximum packet delivery ratio of 93.93 percent, minimum energy consumption of 8.04J, maximum energy efficiency of 91.04 percent, maximum network throughput of 465.51kbps, minimum packet loss of 282 packets, and minimum delay of 63.82 msec.
ENERGY AWARE TALENTED CLUSTERING WITH COMPRESSIVE SENSING (TCCS) FOR WIRELESS...IJCNCJournal
Wireless sensor networks (WSNs) are networks of sensor nodes that interact wirelessly to gather
information about the surrounding environment. Nodes are often low-powered and dispersed in an ad hoc,
decentralized manner. Although WSNs have gained in popularity, they still have several serious
shortcomings, like limited battery life and bandwidth. In this paper, the cluster head (CH) selection, the
Compressive Sensing (CS) theory, the Connection-based Decentralized Clustering (CDC), the relay node
selection, and the Multi Objective Genetic Algorithm (MOGA)are all taken into account The initial stage
provided a theoretical revision to the concepts of network construction, compressive sensing, and MOGA,
which impacted the improvement of network lifetime. In the second stage developed a novel model such as
Energy Aware Talented Clustering with Compressive Sensing (TCCS) for the sensor network. This
approach considers increasing longevity but also raises the network's overall quality of service (QoS). In
the analysis, the TCCS model is applied to both the centralized and distributed networks and compared
with the existing methods. When compared to the previous methods, the simulation results show that the
proposed work performs better in terms of the calculation of maximum packet delivery ratio of 93.93
percent, minimum energy consumption of 8.04J, maximum energy efficiency of 91.04 percent, maximum
network throughput of 465.51kbps, minimum packet loss of 282 packets, and minimum delay of 63.82 msec.
AN EXTENDED K-MEANS CLUSTER HEAD SELECTION ALGORITHM FOR EFFICIENT ENERGY CON...IJNSA Journal
Effective use of sensor nodes’ batteries in wireless sensor networks is critical since the batteries are difficult to recharge or replace. This is closely connected to the networks’ lifespan since once the battery is used up, the node is no longer useful. The entire network will not function if 60 to 80% of the nodes in it have completely depleted their energy. In order to minimize energy usage and sustain the network for a long time, many cluster head selection algorithms have been developed. However, the existing cluster head selection algorithms such as K-Means, particle swarm selection optimization (PSO), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Fuzzy C-Means (FCM) cluster head election algorithm have not fully reduced the issue of energy usage in WSN. The objective of this paper was to develop an extended K Mean Cluster Head selection(CHS) algorithm that uses remaining energy, distance between node and base station, distance between nodes and neighbour nodes, node density, node degree Maximum Cluster size, received signal strength indicator (RSSI) and Signal to Noise Ratio. The algorithm developed was used to enhance the lifespan of WSNs. The performance of the simulated variants of LEACH routing protocols is measured and evaluated using the quantitative research methodology. Utilizing residual node energy, packet delivery ratio, throughput, network longevity, average energy usage, and the number of live and dead node, the suggested approach is contrasted to previous approaches. From the study we observed that the proposed approach outperforms existing actual LEACH, Mod-LEACH and TSILEACH approaches.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
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
Energy efficiency has recently turned out to be primary issue in wireless sensor networks.
Sensor networks are battery powered, therefore become dead after a certain period of time. Thus,
improving the data dissipation in energy efficient way becomes more challenging problem in order to
improve the lifetime for sensor devices. The clustering and tree based data aggregation for sensor
networks can enhance the network lifetime of wireless sensor networks. Non-dominated Sorting Genetic
Algorithm (NSGA) -III based energy efficient clustering and tree based routing protocol is proposed.
Initially, clusters are formed on the basis of remaining energy, then, NSGA-III based data aggregation
will come in action to improve the inter-cluster data aggregation further. Extensive analysis demonstrates
that proposed protocol considerably enhances network lifetime over other techniques.
Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterog...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
SECTOR TREE-BASED CLUSTERING FOR ENERGY EFFICIENT ROUTING PROTOCOL IN HETEROG...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
Hierarchical Coordination for Data Gathering (HCDG) in Wireless Sensor NetworksCSCJournals
A wireless sensor network (WSN) consists of large number of sensor nodes where each node operates by a finite battery for sensing, computing, and performing wireless communication tasks. Energy aware routing and MAC protocols were proposed to prolong the lifetime of WSNs. MAC protocols reduce energy consumption by putting the nodes into sleep mode for a relatively longer period of time; thereby minimizing collisions and idle listening time. On the other hand, efficient energy aware routing is achieved by finding the best path from the sensor nodes to the Base Sta-tion (BS) where energy consumption is minimal. In almost all solutions there is always a tradeoff between power consumption and delay reduction. This paper presents an improved hierarchical coordination for data gathering (HCDG) routing schema for WSNs based on multi-level chains formation with data aggregation. Also, this paper provides an analytical model for energy consumption in WSN to compare the performance of our proposed HCDG schema with the near optimal energy reduction methodology, PEGASIS. Our results demonstrate that the proposed routing schema provides relatively lower energy consumption with minimum delay for large scale WSNs.
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
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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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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.
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The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
** Connect, Collaborate, And Innovate: IJCNC - Where Networking Futures Take ...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Cluster Based Routing using Energy and Distance Aware Multi-Objective Golden Eagle Optimization in Wireless Sensor Network
1. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
DOI: 10.5121/ijcnc.2022.14303 37
CLUSTER BASED ROUTING USING ENERGY
AND DISTANCE AWARE MULTI-OBJECTIVE
GOLDEN EAGLE OPTIMIZATION IN
WIRELESS SENSOR NETWORK
Gundeboyina Srinivasalu1
and Hanumanthappa Umadevi2
1
Department of Electronics & Communication Engineering,
Cambridge Institute of Technology, Bangalore, India
2
Department of Electronics & Communication Engineering,
Dr. Ambedkar Institute of Technology, Bengaluru, India
ABSTRACT
In recent years, WSNs have attracted significant attention due to the improvements in various sectors such
as communication, electronics, and information technologies. When the clustering algorithm incorporates
both Euclidean distance and energy, it automatically decreases the energy consumption. So, the major goal
of this research is to reduce energy consumption for prolong the lifetime of the network. In order to
achieve an energy-efficient process, Energy and Distance Aware Multi-Objective Golden Eagle
Optimization (ED-MOGEO) is proposed in this research. In addition, this proposed solution reduces
retransmissions and delays to improve the performance metrics. And so, this research carried out two
major fitness functions (Euclidean distance and energy) for creating an energy-efficient WSN.
Furthermore, energy consideration is used to reduce the nodes unavailability which results in packet loss
during the transmission. For generating the routing path between the source and the Base Station (BS), the
ED-MOGEO algorithm is used. From the simulation results, it shows that Proposed ED-MOGEO achieves
better performances in terms of residual energy (14.36 J), end-to-end delay (12.9 ms), packet delivery ratio
(0.994), normalized routing overhead (0.11), and throughput (1.131 Mbps) when compared to existing
Cluster-Based Data Aggregation (CBDA) and Elephant Herding Optimization (EHO)-Greedy methods.
KEYWORDS
Multi-Objective Golden Eagle Optimization, Wireless Sensor Networks, Energy Consumption, Network
Lifetime, Euclidean Distance.
1. INTRODUCTION
For the past few years, WSN has a large number of small, low-power sensors that are placed
organized or random manner in the uncontrolled area [1] [2]. Due to their unlimited beneficial in
a variety of applications, including forest life monitoring, military applications, health
monitoring, weather monitoring, and traffic management, WSN has turn out to be an interesting
topic for several scholars [3]. WSN is a network of low-power sensor nodes that are connected by
wireless systems and isolated over through the course of a physical space. These sensor nodes
may collect information from the device, analyse it, send it to the cloud and interact with one
another in order to connect the data acquired to BS [4] [5]. The sensors which are usually fitted
with little batteries that can't be recharged because it has left unattended locations and faster
distribution [6]. As a result, reducing energy usage is the most challenging task in an energy-
2. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
38
constrained networks. Several factors come into play in this situation, still, there have been
several researches focussing on routing protocols for WSNs [7].
WSN sensors can perform sensing, transmission, and computational tasks including data
aggregation and digital signal processing, among other things. The WSN has several
disadvantages, including computing, battery capacity, communication capability, and sensor
mobility [8]. In a hostile environment, sensor reinstallation and charging are not possible, so
energy consumption is a major concern in WSN [9]. To increase the network lifetime, the
aforementioned issue is overcome by clustering the nodes into clusters [10], [11]. In the collected
works, lifetime is determined as the time until the energy of the first sensor's node energy
expires[12]. The sensors are organized into smaller clusters throughout the clustering process,
and a Cluster Head (CH) is picked from each cluster [13]. The cluster members then send the
data packets to their respective CH, which collects and transmits the data to the BS and this is
used to prevent sensor collisions in the WSN [14]. In clustered WSN, the routing protocol is built
for managing CHs and determining the best route for reducing node energy. The data are sent
directly from the CH to the BS in this case or it will be sent through the intermediate CHs [15].
The following are major contributions of this research:
ED-MOGEO is initially utilized for choosing the CH due to its low computational
complexity and excessive stability,
The shortest path from the source to the destination node is discovered using GOE's
quick discovery capability.
As a result, ED-MOGEO-based effective CH selection and optimal route design are used
to extend the network's lifetime.
The organization of this study is stated as follows; Section 2 declared the literature review of
earlier papers associated with clustering and routing. Section 3 describes the problem statement
of this study. The energy model of this research is elaborated in section 4. Section 5 clarified the
equations and working procedure of the proposed methodology. Section 6 signifies the simulation
results along with the comparative study. Lastly, the conclusions are stated in section 7.
2. LITERATURE REVIEW
Nandakishor Sirdeshpande et al. [16] demonstrated a fractional lion optimization method for the
CH-based routing protocol. The proposed Fractional Lion (FLION) clustering algorithm was
designed to provide an energy-efficient routing path. The LION algorithm was combined with the
fractional calculus approach to improve the speed of clustering selection and lower the speed of
searching. The FLION approach had the advantage of maximising the network's lifetime. During
the clustering phase, however, the FLION algorithm lowered the degree of nodes.
Daneshvar [17] proposed the Grey Wolf Optimizer (GWO) selected the CHs in WSN. Proposed
GWOdescription was estimated using the present energy of the node and expected energy usage
in the CH selection. The data packets were then routed via the network using Dual Hop Routing
(DHR). In addition, the GWO method was employed to prevent unnecessary clustering
operations to reduce energy consumption which was considered as main adavantage. The GWO
method ignores the distance factor when picking CHs from the network.
To provide the CH from the nodes, Morsy [18] proposed a hybrid Particle Swarm Optimization
(PSO) and Gravitational Search Algorithm (GSA). The proposed PSO-GSA formula was
employed to determine multi-hop communication between the selected CHS, which is made up
of the CH's residual energy, the distance among the CHs, and the distance between the CH and
3. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
39
the BS. In conclusion, the optimal CH option was chosen to balance energy consumption which
was deliberated as the main advantage. But on the other side, this hybrid PSO-GSA approach has
been unable to evaluate the very last node to die.
Vinitha, Rukmini, and Sunehra [19] presented an energy-efficient routing algorithm based on the
Cat-SSA (C-SSA) algorithm to choose relevant steps throughout the route process. Initially, the
Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol was created to choose the CH in
the network that would reduce network traffic. After reduction, the proposed C-SSA was utilized
to choose a suitable node by eliminating excess energy which was deliberated as a major
advantage. The higher energy consumption was caused by LEACH's random CH selection
characteristic.
Seedha Devi et al. [20] proposed a Cluster Based Data Aggregation Scheme (CDAS) for Packet
Loss and Latency Reduction in WSN. The proposed CDAS structure has two stages: Aggregation
Tree Structure and the Slot Planning Procedure. In the first step, each CH uses compressive
accumulation to collect data from the participants. In the second stage, latency and packet loss are
reserved for analysis, while the acquired data is used to highlight and assign intervals to nodes.
The major advantage of this proposed CDAS was to eliminate unnecessary transmission and
improve the lifetime. But this CDAS procedure was not suitable for all the environments.
Pattnaik and Sahu [21] presented a fuzzy-based clustering approach as well as an Elephant
Herding Optimization (EHO)-Greedy method for routing. To save energy, EHO-Greedy
considers both permanent and portable sinks. A stable node was randomly positioned diagonally
throughout the arrangement, while a portable node shifted into various spots for data collection.
The proposed EHO-Greedy uses a group of CH which can drastically reduce energy usage while
also extending lifespan. In some other applications, the addition of more energy-efficient
techniques leads to larger WSN zones.
3. PROBLEM STATEMENT
The energy efficiency in WSN is calculated by selecting a suitable fitness function. Only the
residual energy of the node is given high significance in the existing approach of clustering.
When the clustering algorithm incorporates both distance and energy, it automatically decreases
the network's energy consumption. In both large and small-scale WSN applications, energy
efficiency must be accomplished. When the number of non-CH members in a CH is large, the
performance of clustering and routing is harmed. The density of the nodes affects the behaviour
as well. Furthermore, when direct data transmission is achieved between the CH and BS, the
WSN's energy dissipation is considerable. This causes the hot spot issue which results in high
packet loss during data transmission. Nodes become unstable and malfunction when it is
deployed in an unmanaged and hostile environment. The WSN considers energy consumption to
be a critical issue during the data transmission phase. A network packet may be dropped if a node
has insufficient energy.
Solution:
The distance of the data transmission channel is directly proportional to the node's energy
consumption. The multi-hop routing is devised in this case to avoid routing difficulties. So, this
study carried out both distance and energy fitness functions for establishing an energy-efficient
WSN, Furthermore, energy consideration is used in the WSN to reduce packet loss. The proposed
ED-MOGEO takes into account a variety of objective functions, including hop count, distance,
4. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
40
and residual energy. As a result, both big and small-scale WSNs use the specified energy-
efficient WSN.
4. ENERGY MODEL
The transmitter and receiver node's energy consumption is calculated using a first-order radio
model. Equations (1) and (2) are used to calculate the amount of energy necessary to send and
receive a packet of l bits across a distance of d .
2
0
4
0
( , ) elec fs
TX
elec mp
l E l d if d d
E l d
l E l d f d d
(1)
( , )
RX elec
E l d l E
(2)
Where, elec
E specifies the energy utilized for transmission/ reception, and 0
d specifies the
threshold distance which is expressed by equation (3).
0
fs
mp
d
(3)
Where, mp
& fs
are the amplification energy for multipath model and free space. The model of
transmitter amplifier defines fs
& mp
.
5. PROPOSED METHOD
Clustering and routing are developed using ED-MOGEO in this study. The algorithm's searching
capabilities were combined with the fitness function values. As a result, in this network, an
effective CH and routing path are chosen. Four distinct fitness function parameters, such as
residual energy, distance, and degree of nodes, are taken into account during the clustering
process. Furthermore, node failure is avoided in the transmission path by taking into account the
nodes' remaining energy. The packet loss is minimized during transmission to prevent node
failure. The major goal of this study is to reduce energy depletion to extend the network's
lifespan. Figure 1 depicts a general flowchart of clustering and routing.
5. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
41
Figure 1. Flowchart of Clustering and Routing using ED-MOGEO
Figure 1 depicts a flowchart for the ED-MOGEO. The following are the steps for the flowchart:
The nodes are first arbitrarily placed in the concerned zone, and then mobile nodes are
defined as a dynamic that is fully dependent on the node's position.
To divide the system into groups, a clustering process is devised. ED-MOGEO is used to
cluster networks in this case. At that moment, CH is determined based on the distance
between neighbours, residual energy, and distance to the base station location, among
other factors.
Routing techniques created using the planned ED-MOGEO which are used to create the
best path between CH and BS.
Starting with the routing process, an ideal node is chosen to create the desired path from
CH to BS.
Once the path from source to destination has been established, the source node sends the
information in the direction of the destination.
This ED-MOGEO finds the best route by taking into account numerous objective
functions such as residual energy, the distance between CH and BS, and hop count.
BS is frequently used to observe the leftover energy of nodes. To avoid network packet
loss, re-clustering/rerouting is done.
5.1. Golden Eagle Optimization (GEO)
The proposed mathematical approach for simulating the motions of golden eagles hunting for
prey is described in this subsection. To emphasize exploitation and exploration, the spiral
motion's formulation is presented below.
6. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
42
5.1.1. Golden eagles motion
The spiral indication of golden eagles stimulated the ED-MOGEO. The golden eagle has the
option of circling its fi memory; hence, 𝑓∈ {1, 2…, 𝑃𝑜𝑝𝑆𝑖𝑧𝑒}.
5.1.2. Choosing the prey
Each memory prey is assigned to the single golden eagle in this approach. The attack and cruise
procedures are then carried out by each golden eagle on the chosen prey.
5.1.3. Attack (exploitation)
The golden eagle attack vector may be estimated using 𝑖 Equation (4).
t f t
A X X
(4)
Where eagle i attack vector is stated as l
A ; best position is signified as f
X ; present position is
stated as l
X . The exploitation phase in ED-MOGEO is highlighted by the attack vector, which
directs the population of golden eagles toward the best-𝑖 frequented places.
5.1.4. Cruise (exploration)
The attack vector is used to determine the cruise vector. In j dimensional space, equation (5) and
(6) shows the scalar arrangement of the hyperplane calculation.
1 1 2 2
1
....
n
n n j j
j
h x h x h x d h x d
(5)
*
1 1
n n t
j j j j
j j
a x a x
(6)
The degrees of freedom for a new point on the n -dimensional cruise hyperplane are 1
n . The
subsequent steps are used to find the location of a golden eagle.
Step 1: Pick one variable at random from the list of variables to serve as the fixed variable. The
attack vector is represented as 𝐴𝑖. The reason for this is that when a variable's coefficient is equal
to zero in 𝐴𝑖 Equation (4),
Step 2: Allocate arbitrary principles for the th
k part, which is fixed.
Step 3. Equation (7) discovers the fixed variable value.
j
jj k
k
k
d a
C
a
(7)
Where k
c is destination point th
cof k element, j
a is the th
j element of the attack vector l
A ,The
attack vector is signified as t
k
a , and fixed variable's index is stated ask . The cruise hyper plane’s
random endpoint is discovered in equation (8).
7. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
43
1 2
, ,... ,,...
j
jj k
i k n
k
d a
C c random c random c c random
a
(8)
5.1.5. Moving to new positions
The golden eagles' movement is made up of two parts: vector and attack. Equation t is the step
vector for eagle i in iteration (9)
1 2
l l
i a c
l l
A C
x r P r P
A C
(9)
Where, attack & cruise coefficient in iteration t is signified as t t
a c
p and p . The random vectors
1 2
r and r have elements that are in the duration [0 1]. Later, a c
P and P can be deliberated. The
Euclidean norms of the attack and cruise vectors ( l l
A and C ) are determined using Equation
(10).
2 2
1 1
n n
l j l j
j j
A a C c
(10)
The golden eagles' position is represented as equation (11).
1
t t t
i
x x x
(11)
The attack coefficient t
a
P and the cruise coefficient t
c
P determine the step vector which is impacted
by cruise and attack vectors, respectively. The following subdivision deliberates in what manner
the two coefficient standards are attuned through the sequence of iterations.
5.1.6. Transition from exploration to exploitation
ED-MOGEO employs a c
p and p a transition from exploration to exploitation. Low a
p and high
c
p are the starting points for the algorithm. a
p Steadily increases whereas c
p gradually decreases
as the iterations progress. The user sets the beginning and end values for both parameters. The
linear transition is shown in Equation which can be used to calculate intermediate values (12).
0 0
0 0
t
a a a a
t
c c c c
t
P P P P
T
t
P P P P
T
(12)
Where t denotes the current iteration, T denotes the maximum iterations, 0 T
c c
P and P denote the
starting and absolute standards for susceptibility to attack ( a
p ), correspondingly. This can be
addressed and reveal that and appear to be appropriate settings. In the first iteration, 𝑝𝑎
progressively decreases until it reaches the last iteration. The same is true for c
p which starts at 1
in the first iteration and decreases linearly until it reaches the last iteration. It's worth noticing that
Equation (12) modifies the constraints linearly.
8. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
44
5.2. ED-MOGEO based Clustering
5.2.1. Fitness function Derivation
The fundamental purpose of the ED-MOGEO-based clustering procedure is to select the best
number of nodes in the neighbourhood, like CHs. The goal is to achieve appropriate fitness by
calculating residual energy, distance, and degree of nodes.
a) Residual energy
The first objective 1
f is signified in Equation (13).
1 1
1
m
i
CHi
Minimize f
E
(13)
b) Euclideandistance
This section explains the Euclideandistance between CH and BS. As previously stated, while
considering energy usage, the sensor node is fully controlled by the transmission distance. When
the base station is further away from the mobile node, it requires more energy to complete the
procedure. As a result, the network estimates the cluster head with the shortest Euclidean distance
which starts from CH to BS. As a result, the next goal is 2
f which can be minimized and written
as an equation (14).
2 1
,
m
j
i
Minimize f dis CH BS
(14)
c) Degree of Nodes
The number of non-CH participants who visit a particular mobile node is referred to as node
degree. If the cluster head has fewer participants, it used to last for a long time, preferring the
lower degree of the node [22]. As a result, in the equation, the third objective 3
f is reduced (15).
1
3
m
i
i
Minimize f I
(15)
Where m refers to number of cluster heads. Accordingly, the normalization process ( ( )
F x ) is
exploited to each objective 1 2 3
, ,
which is shown in (16).
min
max min
( ) i
f f
F x
f f
(16)
Where min max
f and f are quantified as a minimum and maximum fitness value is given in equation
(17).
1 1 2 2 3 3
Minimum fitness f f f
(17)
9. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
45
4
1
1; 0.1
i i
i
Where and
; i
is referred as weighted parameter which is allocated to each
fitness functions ( 1 2 3
0.5; 0.3; 0.2
).
5.2.2. ED-MOGEO based Routing
The major goal of this study is to find a nearby optimum path from each cluster head to the
appropriate BS. The routing amongst the source CH and BS is produced in ED-MOGEO using
the same fitness function that was utilized to select the CH.
5.2.2.1. Initialization
Each ED-MOGEO in routing denotes the data forwarding route from every CH to BS. Each ED-
MOGEO has the same dimensions as the overall amount of CH's present in-network and provides
an extra slot for the BS. The proposed transmission route between the source node and the BS is
updated every moth in the routing process. The quantity of CHs in the associated transmission
route is equal to the measurement of each moth.
5.2.2.2.Route selection
To choose the data transmission path, ED-MOGEO uses the equivalent fitness function (residual
energy, distance, and degree of nodes) that was previously expressed. The Route Request
(RREQ) message is sent from the source node to the neighbour nodes to adjust the route
identification process. At that point, the next node with a higher fitness rating transmits the
message back to source CH through the reverse path. Source CH collects the message from the
neighbouring nodes once the routing path has been created. The data transmission is initiated
through the network after the routing path has been generated.
6. RESULT AND DISCUSSION
The proposed cluster-based routing protocol's results are described in this section. Alive nodes,
energy depletion, delay, overall transmitted packets, throughput, and network longevity are all
used to evaluate the performance. The suggested energy-efficient routing procedure is executed
and confirmed using the MATLAB R2018a program. A Windows 8 PC through an i3
workstation and 4GB RAM is utilized to test the routing protocol. In the ED-MOGEO, an
effective fitness function is used to cluster and route traffic across the network. To imitate the
ED-MOGEO, 100 sensors are placed at random in100 100
m m
region. The simulation
completion time for the proposed ED-MOGEO is quite high, because it estimates the fitness
value in each iteration to find the optimal solutions using ED-MOGEO. Since, this ED-MOGEO
runs till the last node dies, however the simulation of ED-MOGEO depends on the system
configuration level which are observed during testing and evaluation of proposed ED-MOGEO
algorithm. The simulation parameters used in the ED-MOGEO are listed in Table 1.
Table 1. Model constraints
Constraint Value
Packet length 4000 bits
Node Count 100
Initial energy 0.5J
Area 100 100
m m
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46
mp
E 2
10 / /
pJ bit m
fs
E 4
0.001310 / /
pJ bit m
elec
E 50 /
nJ bit
6.1. Performance of Residual energy
Figure 2 depicts the residual energy results for the proposed and conventional CDAS [20]
approaches. When the number of nodes increases, so does the size of the routing path, increasing
delay. The residual energy performance comparison is shown in Table 2. Table 2 demonstrates
that the suggested ED-MOGEO performance ranges from 11.32 to 14.36, whereas CDAS [20]
ranges from 6.4 to 8.
Table 2. Performance of Residual Energy
Number of nodes
Residual Energy (J)
Existing CDAS [20] Proposed ED-MOGEO
50 8 11.32
100 7.5 12.49
150 7 14.02
200 6.4 14.36
Figure 2. Performance of Residual Energy
6.2. Performance of Delay:
The node count is varied from 50 to 200 to study the result of ode density and network size. The
results of delay for suggested and existing approaches are depicted in Figure 3. When the number
of nodes increases, so does the size of the routing path, increasing delay. The end-to-end delay
performance comparison is shown in Table 3. Table 3 indicates that the suggested ED-MOGEO's
delay increases from 7.9 to 12.9 milliseconds, whereas CDAS [20] fluctuates from 9.6 to 14.5
milliseconds.
0
5
10
15
20
50 100 150 200
Residual
Energy
(J)
Number of Rounds
Performance of Residual Energy
Existing CDAS [20] Proposed ED-MOGEO
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Table 3. Performances of Delay
Number of nodes
Delay (ms)
Existing CDAS [20] Proposed ED-MOGEO
50 9.6 7.9
100 11.4 8.2
150 13.1 9.1
200 14.8 12.9
Figure 3. Performance of delay
6.3. Performance of PDR
Figure 4 shows the results of PDR for planned and existing technologies. When the number of
nodes increases, so does the size of the routing path, increasing delay. The performance
comparison for the Packet Delivery Ratio is shown in Table 4. (PDR). Table 4 clearly illustrates
that the suggested ED-MOGEO's PDR ranges from 0.991 to 0.995, whereas CDAS [20]'s PDR
ranges from 0.38 to 0.6, and EHO-PDR Greedy ranges from 0.941 to 0.989.
Table 4. Performances of Packet Delivery Ratio
Number of
nodes
Packet Delivery Ratio
Existing EHO-Greedy
[21]
Existing CDAS [20] Proposed ED-MOGEO
50 0.941 0.6 0.993
100 0.982 0.42 0.991
150 0.987 0.4 0.995
200 0.989 0.38 0.994
9.6
11.4
13.1
14.8
7.9 8.2 9.1
12.9
0
5
10
15
20
50 100 150 200
Delay
(ms)
Number of Rounds
Performance of Delay
Existing CDAS [20] Proposed ED-MOGEO
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48
Figure 4. Performance of PDR
6.4. Performance of Normalized routing overhead:
Figure 5 depicts the results of the Normalized Routing Overhead for proposed and existing
approaches. When the number of nodes increases, so does the size of the routing path, increasing
delay. The performance comparison for Normalized routing overhead is shown in Table 5. Table
5 clearly illustrates that the proposed ED-MOGEO's Normalized routing overhead ranges from
0.11 to 0.31, while CDAS [20] dropped from 0.2 to 0.4.
Table 5. Performances of Normalized routing overhead
Number of nodes
Normalized routing overhead
Existing CDAS [20] Proposed ED-MOGEO
50 0.2 0.11
100 0.26 0.21
150 0.31 0.26
200 0.4 0.31
Figure 5. Performance Analysis of Normalized routing overhead
0.941 0.982 0.987 0.989
0.6
0.42 0.4 0.38
0.993 0.991 0.995 0.994
0
0.5
1
1.5
50 100 150 200
PDR
Number of Nodes
Performance of PDR
Existing EHO-Greedy [21] Existing CDAS [20]
Proposed ED-MOGEO
0
0.1
0.2
0.3
0.4
0.5
50 100 150 200
Routing
Overhead
Number of nodes
Performance of Routing overhead
Existing CDAS [20] Proposed ED-MOGEO
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49
6.5. Performance of Throughput
Figure 6 depicts the results of the throughput performance for suggested and current approaches.
In terms of throughput, the key arguments for the proposed ED-MOGEO achieve better results
than EHO Greedy [21]. The fundamental reason is that ED-MOGEO has a long network lifespan,
which means that the base station receives more data packets. The performance comparison for
Throughput is shown in Table 6. Table 6 reveals that the suggested ED-MOGEO's throughput
reaches a maximum of 1.131 Mbps, whereas EHO-Greedy [21] only managed 1.093 Mbps.
Table 6. Performances of Throughput
Number of nodes
Throughput (Mbps)
Existing EHO-Greedy [21] Proposed ED-MOGEO
50 0.452 1.125
100 0.999 1.131
150 1.074 1.129
200 1.093 1.099
Figure 6. Performance Analysis of Throughput
When compared to the present CDAS approach, the total simulation results show that the
suggested ED-MOGEO gives better results in all node counts (50-200).
6.6. Comparative analysis
The recommended approach receives a significant amount of data packets at the BS due to its
adequate fitness function. In addition, the suggested technique reduces node energy consumption,
allowing nodes to run for extended periods. As a result, there are more living nodes in the
suggested technique. The longer lifetime of the suggested approach is employed to increase the
total number of packets received by the BS. In terms of performance, Table 7 indicates that the
suggested approach beats FLION [16].
0.452
0.999 1.074 1.093
1.125 1.131 1.129 1.099
0
0.2
0.4
0.6
0.8
1
1.2
50 100 150 200
Throughput
(Mbps)
Number of Nodes
Performance of Throughput
Existing EHO-Greedy [21] Proposed ED-MOGEO
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50
Table 7. Comparison of proposed method and FLION
Performance parameters Methods Rounds
500 1000 1500 2000
Alive nodes
FLION [16] 100 80 48 38
Proposed ED-MOGEO 100 100 100 100
Average energy consumption (J)
FLION [16] 0.35 0.15 0.05 0.03
Proposed ED-MOGEO 0.22 0.12 0.04 0.01
To demonstrate the ED-MOGEO method's usefulness, it is compared to two other approaches:
GWO-DHR [17] and C-SSA [19]. In this ED-MOGEO vs. GWO-DHR [17] comparison, 100
sensors are distributed over a network area of 100m100m. As a result, the base station is located
outside of the network expanse, i.e. (150,100). At 100 sensors, 5% of the nodes are selected as
CHs to gather statistics from non-CH associates and deliver them in the direction of BS.
Table 8. Comparative analysis of ED-MOGEO with C-SSA
Rounds Alive nodes Total energy (J) Throughput (Mbps)
C-SSA [19] ED-
MOGEO
C-SSA [19] ED-MOGEO C-SSA [19] ED-
MOGEO
500 47 55 21.5 26.22 15 23
1000 40 55 13 21.53 26 44
1500 34 55 6.5 18.57 40 62
2000 24 55 2.5 15.92 53 87
Table 9. Comparative analysis of ED-MOED-MOGEO with GWO-DHR
Lifetime metrics GWO-DHR [17] Proposed ED-MOGEO
FND 671 1729
HND 778 1866
LND 1286 1899
The ED-MOGEO is compared to the GWO-DHR [17] and C-SSA [19] for alive nodes, total
energy, throughput, and network longevity in Tables 8 and 9. Figure 7 also shows a graphical
representation of the lifetime metric for GWO-DHR and the proposed ED-MOGEO.
Figure. 7 Comparison for ED-MOGEO with GWO-DHR in terms of Lifetime
671 778
1286
1729 1866 1899
0
500
1000
1500
2000
FND HND LND
Rounds
Lifetime Metrics
Comparison of Lifetime
GWO-DHR [17] Proposed ED-MOGEO
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51
Based on the results of the comparison, it was determined that the ED-MOGEO technique
outperforms the GWO-DHR [17]. Due to an incorrect fitness function consideration during CH
selection, the GWO-DHR achieved worse performance. In ED-MOGEO clustering, different
fitness variables are used to discover an appropriate CH between the sensors: residual energy,
intra-cluster distance, distance from the CH to the BS, and node degree. Following that, an
appropriate route creation using the ED-MOGEO is applied to reduce the node's energy
depletion. The simulation result shows that the proposed ED-MOGEO is employed to gain a
longer network lifetime when compared to existing GWO-DHR [17] and C-SSA [19]. The
increased lifetime of the ED-MOGEO is due to the greater volume of data packets sent to the BS.
7. CONCLUSION
WSN are extensively applied in various applications and its sensor nodes are integrated together
to a base station. In this research, ED-MOGEO is proposed which is initially utilized for choosing
the CH due to its low computational complexity and excessive stability. For generating the
routing path between the source and the BS, the ED-MOGEO algorithm is used. Furthermore,
ED-MOGEO method is used to lower total energy usage while extending the life of a network.
Five fitness criteria are used during the ED-MOGEO-based CH selection: residual energy,
distance to the BS, distance to the neighbours, node centrality, and node degree. ED-MOGEO is
applied to achieve an energy efficient route selection using the leftover energy, number of hops,
and distance. The proposed ED-MOGEO outperforms existing protocol systems in all features,
according to simulation results, by lowering delay and normalized routing overhead to 12.9 ms
and 0.11, respectively. It also has a 14.36 J residual energy, a maximum PDR of 0.994, and a
throughput of 1.131 Mbps. In the future, the proposed methodology can be analysed with
different specification parameters, node counts, as well as a novel routing procedure to produce
better energy efficient results.
Notations
Notation Description
𝑑 Distance
𝐸𝑒𝑙𝑒𝑐 Energy utilized for transmission/reception
𝑑0 Threshold distance
𝜀𝑚𝑝 Amplification energy for multipath model
𝜀𝑓𝑠 Amplification energy for free space
𝑓𝑖 Circling option
𝐴𝑖
⃗⃗⃗ Attack Vector
𝑋𝑓
⃗⃗⃗⃗ Best Position
𝑋𝑖
⃗⃗⃗ Current Position
𝑛 − 1. Degree of freedom on 𝑛-dimensional cruise
hyperplane
𝑘 Fixed variable's index
𝑐𝑘 Destination point
𝐶𝑖
⃗⃗⃗ cruise hyper plane’s random endpoint
‖𝐴𝑖
⃗⃗⃗ ‖ The Euclidean norms of the attack vectors
‖𝐶𝑖
⃗⃗⃗ ‖ The Euclidean norms of cruise vectors
𝑥𝑡+1 Position of golden eagle
𝑃𝑎
𝑡 Attack coefficient
𝑃𝑐
𝑡 Cruise coefficient
16. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.3, May 2022
52
CONFLICTS OF INTEREST
The authors declare no conflict of interest.
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𝑚 Number of cluster head
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AUTHORS
G Srinivasalu received the B E degree in Electronics Engineering from Bangalore
University, M E degree in Digital Communications from Bangalore University.
Currently he is serving as Associate Professor, Department of Electronics &
Communication Engineering, Cambridge Institute of Technology, Bangalore. He has
20 years of teaching UG and PG students. Teaching subjects Include Digital
Communications, Wireless Communications, Wireless Sensor Networks. His research
interests include Digital signal processing, Digital communications, Wireless
communications
H. Umadevi received the BE degree in Electronics & Communication Engineering
from Mysore University, ME degree in Electronics from Bangalore University and Ph.
D degree in wireless communications from Bangalore university. Currently she is
currently serving as Professor, Dept. of Electronics & Communication Engineering,
Dr. Ambedkar Institute of Technology, Bangalore. She has 25 years of teaching
experience she teaches undergraduate and postgraduate courses and is supervising
Ph.D. students. She has published more than 50 papers in reputed journals. She is
chairperson for many national and international conferences. She has Received Women researcher award in
International Scientist Awards on Engineering, Science and Medicine in 2020.