Research On Wireless Sensor Network Routing Protocal Optimization Algorithm

Wireless sensor network has emerged in the1980s to90s, the first used in military. Since the21st century, the wireless sensor network with its self organization, node design low powerconsumption and some others characteristic, its application field is more and more widely. Thetechnology used in the information technology and economic life has important influence on humanlife and social progress. Therefore, this technology also has been paying much attention to researchtopic by domestic and overseas scholars. Because wireless sensor network usually work inunmanned surveillance area,and node energy can only rely on battery power, so reduce the energyconsumption and prolong the network lifetime has been the focus of research. This paper, first of all,in.depth analysis the existing wireless sensor classical routing protocol algorithm, in view of thenow wireless sensor network routing protocol clustering algorithm cluster head uneven distribution,energy consumption not equilibrium problems, put forward a new routing protocol based onLEACH algorithm. And the particle swarm optimization (pso) algorithm and ant colony algorithmis introduced into the routing process.This thesis proposed a new routing protocol algorithm, using the monitoring area according to the percentageof clusters divided into several small area. In a small area, each area only select one cluster head nodes. Becausecluster head bear more the task than the ordinary node,so they consume more energy.when we selects cluster head,trying to choose the nodes which has high residual energy. After the establishment of the cluster,cluster headtransmit data to sink node in routing relay method. This paper will introduce ant colony algorithmto find the optimal path. When choosing a next node, we not only considers distance factors, butalso the energy is also taken into consideration.This means that the path should not only as soon aspossible, and the rest of the energy as much as possible. At the same time for ant colony algorithmexcessive dependence on the parameters, we let particle swarm optimization (pso) algorithm trainant colony optimization parameters, adaptive guidance on the selection of parameters.Finally compared with LEACH algorithm in the average energy consumption of network, thenode number, survival and scalability for experimental analysis. The experiments show that the improvedalgorithm in energy equilibrium consumption and prolong the network life is better than LEACH, and moresuitable for monitoring large area. This shows that througth the well.distributed cluster head and using particleswarm and ant colony algorithm to find the best path method to save energy and prolong the network life cyclehas good performance.