Coverage Control Algorithm for Heterogeneous WSN based on Multi-objective Tuna Swarm Optimization

In order to solve the coverage hole problem caused by random deployment of WSN nodes, aiming at the demand of energy consumption optimization in the process of redeployment, the coverage control problem is constructed as a multi-objective optimization problem, a coverage control algorithm for heterogeneous WSN with normal distribution of node perception radius is proposed. Firstly, in order to enrich the diversity of tuna population, the Sobol sequence was used for initialization in the initial stage. In addition, nonlinear weight coefficient is introduced to comprehensively consider the global search and local development ability of the algorithm. Secondly, the fast non-dominated sorting method is used for reference to classify the tuna population, and elite reservation and external archiving strategy are added to improve the accuracy of the algorithm. Then, a reasonable calculation method of crowding distance is proposed to enhance the diversity of optimal solutions. Finally, in the Matlab simulation environment, the NSMTSO, NSGA-II, NSMOFPA and MOPSO algorithm are tested in the standard test function and WSN coverage optimization respectively. The simulation results show that the NSMTSO algorithm proposed in this paper is more stable, and the optimal solution set obtained is more competitive in convergence and distribution.