Research on WSN Coverage Based on Improved Snake Optimizer Algorithm
In order to effectively improve the coverage effect and increase the connectivity among nodes when wireless sensor network(WSN)are deployed,a multi-objective deployment optimization strategy of nodes based on the improved snake optimization algorithm is proposed.In the population initialization phase,the Halton sequence initialization strategy is introduced to initialize the population indi-viduals for the uneven distribution of the random population initialization of the snake optimization algorithm,and to make each node of the population have the randomness characteristics within a certain interval,which not only ensures the uniform distribution within the ini-tialized population individuals,but also makes the diversity among individuals.In the development phase,a new foraging strategy is proposed to replace the original foraging phase,which can prompt individuals to quickly jump out of the local optimum.In the mating mode of the development phase,a heterosexual attraction strategy is proposed to replace the mating strategy,so that the algorithm has a stronger global exploration and exploitation capability.Then,we will compare the proposed algorithm with the basic snake optimization algorithm,the single-stage improved snake optimization algorithm and other improved optimization algorithms.The simulation results show that the improvement strategies in different stages have different degrees of influence on the improved algorithm.In addition,the improved algorithm outperforms other improved optimized deployment algorithms in terms of wireless sensor network coverage optimization performance.
万方数据
维普
