An Improved Bat Algorithm for Unequal Clustering in Heterogeneous Wireless Sensor Networks

Abstract

Clustering is one of the imperative solutions to the problem of energy unbalancing prevailing in the network. The major issues of wireless sensor network with unequal clustering and multi-hop communication are the energy stability and network longevity. In this paper, we consider the improved Bat optimization algorithm to improve the unequal clustering techniques by forming groups before selecting Cluster Heads. In terms of saving energy, knowing the positions of sink nodes in WSNs plays a vital role. Bat algorithm (BA), optimization of particle swarm, differential evolution, and whale optimization algorithm is now becoming efficient clustering methods as per the metaheuristic approach. Evaluate the life span of the entire network; this paper proposes an improved BA. The BA's primary goal of unequal clustering is to reduce energy consumption and extend the lives of the WSNs. An objective function has been formulated to reduce energy consumption and increase the network's lifespan to achieve these goals. Compared with three existing optimization methods, the experimental results showed that the proposed improved BA achieved better efficiency in reducing total power consumption: whale optimization for topology control, and improved particle swarm optimization algorithm.

An effective hotspot mitigation system for Wireless Sensor Networks using hybridized prairie dog with Genetic Algorithm

“…The simulation is investigated for approaches, namely HM-PGA and existing techniques, specifically, Tunicate Swarm Algorithm (TSA) [ 25 ], Distributed Ant Colony Optimization-based Routing (DACOR) protocol [ 29 ], and Political Optimizer-based Unequal Clustering Scheme (POUCS) [ 33 ]. Several key metrics are employed to assess the HM-PGA model’s performance comprehensively.…”

“…Authors in [ 33 ] used a Political Optimizer-based Unequal Clustering Scheme (POUCS) to mitigate hotspot issues in WSN. The POUCS technique aims to select CHs and find variable cluster sizes.…”

Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

“…Moreover, for optimal route solution, the harmony search (HS) route selection method can be derived. In a previous study, 12 the authors consider the enhanced bat optimization algorithm (BA) for enhancing the UEC techniques by constituting groups before the selection of the CHs. The BA, optimization of whale optimization algorithm, particle swarm optimization (PSO), and differential evolution are now potential clustering techniques according to the metaheuristic algorithm.…”

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

“…Hierarchical clustering is effective at the level of managing the topology of the networks. Changes in cluster membership should be reported to the base station, as re-clustering is required to maintain the effectiveness of the topology [32].…”