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A novel energy-efficient clustering protocol in wireless sensor network: multi-objective analysis based on hybrid meta-heuristic algorithm

A novel energy-efficient clustering protocol in wireless sensor network: multi-objective analysis... Energy efficiency is one of the major challenges in the growing WSNs. Since communication offers a vast place in the consumption of energy, effective routing is the best solution to handle this problem. The lifetime improvement is an important problem since the majority of the WSNs function in an unattended environment, in which monitoring, as well as human access, is not possible in a practical manner. Clustering is one of the powerful approaches, which arranges the system operation for the enhanced lifetime of the network, improves energy efficiency, reduces the consumption of energy, and also attend the scalability of the network. To handle this issue, the present researchers have considered the usage of various clustering algorithms. Yet, the cluster head is burdened by the majority of the suggested algorithms in the process of cluster formation. To handle this problem, this paper plans to develop the energy-efficient clustering for WSN using the improved LEACH protocol. Here, the concept of a hybrid meta-heuristic algorithm is used for the optimal cluster head selection through energy-efficient clustering. The optimal solutions are rated based on the multi-objective function considering the objective constraints like energy, distance, delay, quality of service (QoS), load, and time of death. Communication between the sink node and cluster head uses the distance of separation as a parameter for reducing energy consumption. Two well-performing algorithms, like salp swarm algorithm (SSA) and grasshopper optimization algorithm (GOA) are merged to develop the proposed hybrid algorithm called salp-swarm grasshopper optimization (SS-GO). From the results, for 200 nodes, the normalized energy of SS-GO at 1400th round is 5.41%, 11.43%, 14.71%, and 25.81%, superior to GOA, SSO, O-EHO, and FU-CSA, respectively. Here, the performance of the proposed SS-GO is also higher in the other distance, delay, time of death node, and QOS. The performance of the introduced hybrid algorithm-based LEACH is evaluated in several different scenarios, and it is shown that the proposed protocol improves network lifetime in comparison to a number of the recent similar protocol. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Reliable Intelligent Environments Springer Journals

A novel energy-efficient clustering protocol in wireless sensor network: multi-objective analysis based on hybrid meta-heuristic algorithm

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References (40)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021
ISSN
2199-4668
eISSN
2199-4676
DOI
10.1007/s40860-021-00159-w
Publisher site
See Article on Publisher Site

Abstract

Energy efficiency is one of the major challenges in the growing WSNs. Since communication offers a vast place in the consumption of energy, effective routing is the best solution to handle this problem. The lifetime improvement is an important problem since the majority of the WSNs function in an unattended environment, in which monitoring, as well as human access, is not possible in a practical manner. Clustering is one of the powerful approaches, which arranges the system operation for the enhanced lifetime of the network, improves energy efficiency, reduces the consumption of energy, and also attend the scalability of the network. To handle this issue, the present researchers have considered the usage of various clustering algorithms. Yet, the cluster head is burdened by the majority of the suggested algorithms in the process of cluster formation. To handle this problem, this paper plans to develop the energy-efficient clustering for WSN using the improved LEACH protocol. Here, the concept of a hybrid meta-heuristic algorithm is used for the optimal cluster head selection through energy-efficient clustering. The optimal solutions are rated based on the multi-objective function considering the objective constraints like energy, distance, delay, quality of service (QoS), load, and time of death. Communication between the sink node and cluster head uses the distance of separation as a parameter for reducing energy consumption. Two well-performing algorithms, like salp swarm algorithm (SSA) and grasshopper optimization algorithm (GOA) are merged to develop the proposed hybrid algorithm called salp-swarm grasshopper optimization (SS-GO). From the results, for 200 nodes, the normalized energy of SS-GO at 1400th round is 5.41%, 11.43%, 14.71%, and 25.81%, superior to GOA, SSO, O-EHO, and FU-CSA, respectively. Here, the performance of the proposed SS-GO is also higher in the other distance, delay, time of death node, and QOS. The performance of the introduced hybrid algorithm-based LEACH is evaluated in several different scenarios, and it is shown that the proposed protocol improves network lifetime in comparison to a number of the recent similar protocol.

Journal

Journal of Reliable Intelligent EnvironmentsSpringer Journals

Published: Dec 1, 2022

Keywords: Energy-efficient clustering protocol; Wireless sensor network; Multi-objective analysis; Salp-swarm grasshopper optimization

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