Localization in 3D Sensor Networks Using Stochastic Particle Swarm Optimization
Localization is one of the key technologies in wireless sensor networks,and the existing PSO-based localization methods are based on standard PSO,which cannot guarantee the global convergence.For the sensor network deployed in a three-dimensional region,this paper proposes a localization method using stochastic particle swarm optimization.After measuring the distances between sensor nodes,the sensor nodes estimate their locations using stochastic particle swarm optimization,which guarantees the global convergence of the results.The simulation results show that the localization error of the proposed method is almost 40% of that of multilateration,and it uses about 120 iterations to reach the optimizing value,which is 80 less than the standard particle swarm optimization.
wireless sensor network localization stochastic particle swarm optimization
ZHANG Zhangxue CUI Huanqing
Fujian Institute of Scientific and Technology Information,Fuzhou 350003,Fujian,China;Fujian Strait I Shandong Computer Science Center,Shandong Provincial Key Laboratory of Computer Network,Jinan 250014
国内会议
福州
英文
544-548
2012-10-27（万方平台首次上网日期，不代表论文的发表时间）