The coverage optimization for underwater sensor networks based on SAPSO algorithm

Abstract

The coverage of underwater sensor network (UWSN) is a basic problem of underwater wireless sensor network, which is related to the integrity and accuracy of underwater sensor network data collection for target monitoring area. In addition, the working environment of underwater sensor nodes is often harsh and the influencing factors are complex, which is not convenient for frequent battery replacement. Therefore, optimizing the coverage of underwater sensor networks can effectively improve the monitoring quality and lifetime of UWSN. Aiming at the shortcomings of previous coverage optimization algorithms, such as easy to fall into the local optimal solution, complex parameters and slow convergence speed, this paper proposes a simulated annealing particle swarm optimization algorithm (SAPSO), which improves the particle swarm optimization algorithm (PSO) by introducing simulated annealing algorithm, so that the algorithm can maintain a faster convergence speed and overcome the shortcomings of PSO algorithm easy to fall into the local optimal solution, so as to improve the coverage of underwater sensor networks, It also makes the distribution of nodes more uniform and reduces the network energy consumption. Simulation results show that SAPSO algorithm can effectively improve the coverage rate of target monitoring area, reduce the redundancy of node coverage and reduce the network energy consumption.