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Improved Salp Swarm and Bare Bones Mayfly Optimization Algorithm-based CH Selection and Sink Node Mobility for improving Network Longevity in WSNs
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Improved Salp Swarm and Bare Bones Mayfly Optimization Algorithm-based CH Selection and Sink Node Mobility for improving Network Longevity in WSNs
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Improved Salp Swarm and Bare Bones Mayfly Optimization Algorithm-based CH Selection and Sink Node Mobility for improving Network Longevity in WSNs
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Journal Article
Improved Salp Swarm and Bare Bones Mayfly Optimization Algorithm-based CH Selection and Sink Node Mobility for improving Network Longevity in WSNs
2025
Overview
Energy-potent routing protocols are vital for extending lifetime and energy stability in Wireless Sensor Networks (WSNs) as they comprise of numerous tiny sensor nodes with limited battery-powered energy. Clustering is a significant strategy that is commonly used for balancing energy consumption among energy-restricted sensor nodes with minimized overhead and traffic during data transmission. In particular, using a hybrid Swarm Intelligence (SI) metaheuristic algorithm for clustering and Cluster Head (CH) selection are considered to be significant for improving network longevity. In this paper, an Improved Salp Swarm and Bare Bones mayfly Optimization Algorithm (ISSBBMFOA)-based CH selection, along with sink node mobility scheme is proposed for improving network longevity. This algorithm specifically uses Improved Salp Swarm Optimization Algorithm (ISSOA) for identifying potential CH nodes in the network. This selection of CHs completely depends on the evaluation of fitness factors such as load balancing, mean inter and intra-cluster distances, distance from the sink and nodes’ Residual Energy (RE). It adopts Bare Bones Mayfly Optimization Algorithm (BBMFOA) for determining movement trajectory and location of sink corresponding to each cluster, following clustering of network regions involving optimal clusters. It facilitates moving sink to stop at optimal locations and aggregate data from sensor member nodes of associated clusters. The simulation results of the proposed ISSBBMFOA scheme confirm 23.21% improved throughput, 24.84% better sustained alive nodes and 22.62% enhanced network lifetime in contrast to other CH selection schemes considered for investigation.
Publisher
Springer India,Springer Nature B.V
