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Hybrid metaheuristic algorithm for optimal cluster head selection in wireless sensor network
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DOI：10.1016/j.pmcj.2021.101504.png)
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Clustering is one of the major techniques for maximizing the network lifetime in wireless sensor networks (WSNs). Here, the sensor nodes (SNs) are grouped into clusters and the cluster heads (CHs) are selected for each cluster. CHs gather data from particular cluster nodes and then forward it to Base Station (BS). However, the selection of CHs is the major issue in this scenario. The sensor nodes consume more energy for the data transmission and also affect the lifetime of the network. The clustering technique is used to provide the energy-efficient data transmission that consumes less energy and also increases the network lifetime. This paper aims to propose a new energy aware CH selection framework by hierarchical routing in WSN via a hybrid optimization algorithm. Moreover, the selection of CH is carried out under the consideration of energy, distance, delay and Quality of Service (QoS) as well. For selecting the optimal CH, a new hybrid algorithm named as Particle Distance Updated Sea Lion Optimization (PDUSLnO) algorithm is introduced that combines the concept of Sea Lion Optimization (SLnO) and Particle swarm optimization (PSO) algorithm. Finally, the performance of adopted method is computed over other traditional models with respect to certain metrics. (C) 2021 Elsevier B.V. All rights reserved.
Keyword:
Clustering
Base station
Hierarchical routing
Optimization
Quality of Service
期刊
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3.5
论文数:
1.5K
被引数:
2.2K
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