An Networking And Optimization Problem Based On Particle Swarm Algorithm

Wireless sensor network(WSN)is a distributed wireless network and it consists of a large number of sensor nodes deployed in a certain area by running the related network algorithm,and the researches of it is an important subject.For sensor nodes,they are usually powered by limited batteries and usually deployed in a harsh environment.The design of energy efficient routing protocol is the primary target of wireless sensor network energy supply constraints.This dissertation first introduced the wireless sensor network application field,research status and the related concept of the network.Analyzing the networking algorithm of wireless sensor network(WSN)in present stage and its disadvantages,and designing an efficient coding scheme based on particle swarm clustering network algorithm.Finally,in combination with the actual work of network background to the simulation of algorithm,the convergence speed and the networking performance of the algorithm is analyzed.For WSN,how to implement the optimal clustering and prolong the network lifetime,the networking algorithm regard to prolong the network lifetime,the equilibrium of each node energy consumption and the efficiency of network data transmission as for the basic goal of solving clustering problem.This dissertation presents Nonlinear Programming formulations of the network deployment.The clustering algorithm will be used to solve these problems.The simulation results show that the algorithm has resolved the shortcomings that clustering unreasonable and cluster head choosing defect of WSN without gateways.The clustering algorithm makes the WSN more balanced and efficient in energy consumption and prolong the lifetime of the network.For the insufficiency of the networking algorithm base on the standard particle swarm algorithm,a improved networking algorithm is proposed,it improves the update strategy of the networking algorithm and divides the whole swarm into subgroups.Every particle can refer to the global optimal solution and the individual optimal solution,the improved algorithm be called cooperative evolution between clustering particle swarm optimizer(CEBCPSO).The algorithm improves initial solution generate strategy,individual update and conducts networking operation with the optimal clustering theory.According to the simulation results,the proposed algorithm are compared with the standard particle swarm optimization in terms of the convergence of the algorithm,energy consumption and improving survival.According to requirements,we use embedded development boards as wireless sensors to design a WSN with some terminal nodes and simulate the algorithm in the network.The experimental results show that the algorithm can control the data transmission in the wireless network effectively.