Design And Implementation Of Clustering Algorithm For Energy Optimization Based On ZigBee

With the continuous development of wireless sensor network technology and perfect, more and more fields need to use this technology, so that all countries in the world as a key research field, however, with an increasing incidence of its application field, carrying capacity is limited, the node can cause problems such as short life network also stand out, these problems seriously restricted the wireless sensor network technology is widely used. How to use routing protocols to reduce the node energy consumption, the balance of the whole network energy consumption has been a hot topic in the research of relevant areas.LEACH protocol is now more classic and widely used in wireless sensor network(WSN) of a routing protocol, it obvious effects in improving the node energy consumption problem, but the algorithm also exist, such as cluster heads is randomly generated, the cluster head election without the residual energy of the current node as the cluster distribution in the whole network reference conditions and the balance is not good, these problems of the network energy consumption is not balanced, which will affect the service life of the network.This article adopts the method of combining theoretical analysis and simulation verification to LEACH agreement was improved, LEACH-PDQ algorithm, by introducing particle swarm algorithm in its cluster process optimal cluster Numbers,dual cluster head to transmit data and USES the data fusion and jumped and the transmission mode of combining not only makes the cluster head election more scientific, the size of the cluster and distribution more reasonable at the same time also can balance the energy consumption of the nodes in a network, prolonging the life of the network.The simulation using the MATLAB software right by the several important performance index for the simulation of the agreement. And the improved LEACH-PDQ algorithm compared with LEACH algorithm of index, the experimental results show that the improved method of clustering is more uniform and reasonable, not only effectively reduce the network energy costs, but also can make balanced energy consumption, and prolong the life of the network.