Modified Parallel Tunicate Swarm Algorithm and Application in 3D WSNs Coverage Optimization

Abstract

As the application of Wireless Sensor Networks (WSNs) in today's society becomes more and more extensive, and the status is getting higher and higher, the node layout of sensors has also begun to attract social attention. In reality, the coverage of WSNs in 3D space is particularly important. Therefore, it is worth investigating an efficient way to find out the maximum coverage of WSNs. In this paper, a Modified Parallel Tunicate Swarm Algorithm (MPTSA) is proposed based on modified parallelism, which can improve the convergence of the algorithm and optimal global solution. Next, the proposed MPTSA is implemented and tested on 23 benchmark functions to verify the algorithm performance. Finally, a WSNs network layout scheme based on MPTSA is proposed to improve the coverage of the whole network. Experimental results show that, compared with the traditional PSO (Particle Swarm Optimization), improved PSO (PPSO and APSO), GBMO (Gases Brownian Motion Optimization) and traditional TSA, MPTSA family algorithms show better performance in WSNs network layout.