Optimizing the Industrial Wireless Sensor Network Connectivity Using Improved Whale Optimization Algorithm

This paper aims to develop an improved whale optimization algorithm (IWOA) to enhance the industrial wireless sensor networks (IWSN) field device placements to achieve effective network connectivity and coverage for all the available clients in its network. The proposed IWOA is created using mathematical functions such as square, cube, and square root as the stochastic accelerator scaling coefficient parameter. As a result of using different benchmark test functions, the proposed algorithm is evaluated against the conventional whale optimization algorithm. In addition, the algorithm is further validated using the IWSN issues like the optimal placement of sensor nodes, adequate client coverage, and network overlapping. The results show that the proposed algorithm showed 64.51% increased client connectivity and network coverage. In the optimization test functions, IWOA achieved a 143.15% performance increase in finding the best global minima values in fewer iterations.