Improved Whale Optimization Algorithm for Optimal Network Coverage in Industrial Wireless Sensor Networks

This paper aims to develop an improved whale optimization algorithm (IWOA) using naturally occurring spiral characteristics for optimal router placement in the industrial wireless sensor networks (IWSN) with adequate network connectivity and coverage for all the available clients in its network. The proposed algorithm uses the widely known Archimedean spiral characteristics for the humpback whale’s bubble-net hunting behaviour. The proposed algorithm is compared with the existing whale optimization algorithm (WOA) over multiple optimization benchmark test functions using various spiral patterns. Furthermore, the algorithm is additionally validated for the IWSN problem to obtain the optimal locations for placing the routers in the network to provide maximum connectivity and client coverage for all the available clients with possible minimization of the area overlapping. The numerical and convergence results show that using sin and cos based spiral behaviours improved the convergence rate by 42.866% and 100% in benchmark test functions and IWSN problem, respectively.