An Improved PSOGSA for Clustering and Routing in WSNs
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An Improved PSOGSA for Clustering and Routing in WSNs Tanima Bhowmik1 · Indrajit Banerjee1 Accepted: 29 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Wireless sensor network (WSN) is an integration of sensing, communicating, computing in a board range environment. Efficient energy consumption becomes the most challenging task for sensor nodes. The clustering and routing techniques are promising methods to resolve the issue and extend the network’s lifespan. The clustering technique is defined as grouping data into classes, every cluster sharing a high degree of similarity in between them, and each cluster being dissimilar with others. This technique is the best data processing model for WSN, and it controls the redundant data inside the network. The nomination of the appropriate cluster head is a major factor in the clustering technique. The object of this proposed paper is to equipoise the energy of the clustering nodes and route the data from cluster head to sink. We propose an improved particle swarm optimization gravitational search algorithm for clustering and routing in WSNs. Here clustering algorithm makes equal energy in the entire network by the uniform distribution of cluster head, routing algorithm decides the ideal routing path to convey data packet between cluster head and sink. The proposed paper integrates the exploration capacity of GSA and the exploitation capability of PSO. Detailed simulation performs using MATLAB based simulator in terms of residual energy, network lifespan, and convergence rate. In comparing our proposed algorithm to other existing algorithms, it outperforms significantly. Keywords Wireless sensor network (WSN) · Clustering · Routing · Particle swarm optimization · Gravitational search algorithm · Fitness function
1 Introduction The wireless sensor network (WSN) consists of several portable low cost, minimum powered sensor nodes haphazardly installed in an environment to capture the data and convey it to the sink for processing. WSN is utilized in various areas to serve a largescale demand. They are applied in disaster management systems, location monitoring systems, health care, security, and tactical areas such as defense surveillance [1]. As * Tanima Bhowmik [email protected] Indrajit Banerjee [email protected] 1
Department of IT, IIEST Shibpur, Howrah, India
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they are deployed in remote places, so it is impossible to charge or replaced the batteries. If any node is damaged, then it can affect the whole network. The main key issue in WSN is energy consumption that has a straight affect on network coverage. The proposed paper aims at optimizing energy consumption, and enhancing the network’s lifespan. The integration of clustering and routing is an efficacious scheme to diminish energy consumption, lengthen the network’s lifespan [2–4]. In this process, sensor nodes are assembled into small sets entitled as clusters. From all the clusters, the mightiest one is
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