Multiobjective Optimization Strategy of WSN Coverage Based on IPSO-IRCD

The nonuniform distribution characteristic of randomly deployed mobile nodes will lead to the coverage hole and redundancy in wireless sensor networks (WSNs). To solve this problem, we propose a multiobjective optimization algorithm for WSN based on Improved Particle Swarm Optimization-Increment Ratio Coverage Rate Move Distance (IPSO-IRCD), network node model is formulated maximize rate target area while reducing moving distance nodes. In each iteration IPSO, population fitness value calculated compared with historical optimal value, when arbitrary dimensional location information updated, which can avoid standard PSO loses solution, IPSO determine candidate deployment Based which, IRCD scheduling proposed, so that final be determined iteratively by calculating Simulation results indicate that, initial state follows random Gaussian distribution, IPSO-IRCD can, respectively, improve 4.6% 7.4% ratio suboptimal other five similar algorithms reduce 809.59 m 626.63 distance.