An Improved Salp Swarm Algorithm for Solving Node Coverage Optimization Problem in WSN

In order to improve the coverage of wireless sensor networks and reduce the energy consumption of node movement in secondary deployment, an improved coverage optimization algorithm based on improved Salpa swarm Intelligent algorithm (ATSSA) is proposed. Firstly, the population is initialized using tent chaotic sequence to enhance the optimization ability of the algorithm. Secondly, the T-distribution mutation is added to the update formula of the leaders for improving the ability to jump out of the local optimal value. Finally, an adaptive formula for updating the position of the follower is proposed, which not only guarantees the local searching ability of the algorithm in the late iteration period, but also improves the global searching ability of the algorithm in the early iteration period. The experimental results show that ATSSA algorithm can improve the coverage of the wireless sensor networks and reduce deployment costs compared with other algorithms, when it is used in the wireless sensor networks.