Wireless sensor node localization based on IPSO-MC

Wireless sensor node localization based on IPSO-MC

Blog Article

To solve the problem of insufficient node positioning ORG CHICK PEAS accuracy in wireless sensor networks,an algorithm based on improved particle swarm optimization by membrane computing (IPSO-MC) was proposed.Kent mapping was used to initialize the population and domain particles were introduced to improve the global optimization of the particle swarm.The weight factor and nonlinear extreme value perturbation were used to improve the local optimization ability of the particle swarm,and the Levy flight mechanism was used to optimize the individual position.Finally,the optimal solution of the particle swarm algorithm was obtained by the evolutionary rules of the membrane computing.

Simulation experiments show that compared with the chicken flock algorithm,the improved particle swarm algorithm and the membrane computing,the proposed algorithm improves 3.24%,5.12% and 8.15% in the comparison of reference node ratio indicators,and the NEFF N1AHA02N0B N50 Built In 59cm Warming Drawer Stainless Steel increase in the number of nodes indicators by 2.

26%,7.82% and 9.81%,and the comparison of communication radius indicators increased by 2.15%,5.

5% and 7.5%,respectively.This indicates that the algorithm has a good effect in node localization.