Wireless Sensor Network Energy Optimization Based On Improved Particle Swarm Optimization Algorithm

Wireless sensor network (WSN) is self-organized by a huge number of sensor nodeswhich is uniformly distributed in monitoring area. The sensor node is composed of sensors,data processing module and communication module. Wireless sensor network has beenwidely used in environmental monitoring, climate control, home remote control, intelligentalarm, equipment maintenance, medical diagnosis, etc, now. A sensor node has limitedenergy, and the deployment environment is difficult to replace or supplement. Therefore，it isthe research priority in WSN how to use the limited energy effectively and balancedly andprolong the network lifetime.This article is based on wireless sensor network. Using intelligent algorithm to optimizethe classic LEACH to prolong the network’s lifetime. The main contents are as follows:1、 This paper summarizes the basic situation of the wireless sensor network andintroduce briefly the research situation at home and abroad. Mainly introduces the operatingmechanism of LEACH routing protocol, and analyzes the advantages and disadvantages ofLEACH.2、 For the clusterheads selection mechanism of LEACH routing protocol, which don’tconsider the residual energy of nodes and the communication distance between cluster headsand Base Station(BS), will lead nodes dead early. Using location weighted particle swarmoptimization combines with the fitness function which contains the remaining energy, thedistance between the cluster heads and BS and the distance of the clusters’ nodes. To verifythe feasibility of the improved algorithm compares with LEACH routing protocol and DCHSrouting protocol through MATLAB simulation platform.3、 It proposes an improved protocol based on the new chaotic particle swarm algorithmand ant colony algorithm for optimization utilization of energy of LEACH routing protocol.Firstly, using the new chaotic particle swarm optimization algorithm, which can help particlesjump out local optimum and improve search precision,selects the appropriate cluster heads.Then using ant colony optimization algorithm combined with nodes’ residual energy andmulti hop communication distance to find the best multi hop paths. Finally,compared in twomonitoring scope, the result shows that the improved algorithm can get better result in lagermonitoring scope.