[1]王东东,崔宝同.基于自适应粒子群优化的WSN分簇路由协议研究[J].计算机技术与发展,2014,24(03):82-85.
　WANG Dong-dong,CUI Bao-tong.Research of WSN Clustering Routing Based on Adaptive Particle Swarm Optimization[J].,2014,24(03):82-85.
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基于自适应粒子群优化的WSN分簇路由协议研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年03期
页码:
82-85
栏目:
智能、算法、系统工程
出版日期:
2014-03-31

文章信息/Info

Title:
Research of WSN Clustering Routing Based on Adaptive Particle Swarm Optimization
文章编号:
1673-629X（2014）03-0082-04
作者:
王东东; 崔宝同
江南大学 物联网工程学院
Author(s):
WANG Dong-dong; CUI Bao-tong
关键词:
无线传感器网络; 基本粒子群算法; 自适应权重; 变学习因子; 改进粒子群算法
Keywords:
WSN; BPSO; adaptive inertia weight; variable study factor; AWSPSO; Leach
分类号:
TP301.6
文献标志码:
A
摘要:
为了克服基本粒子群算法( BPSO)的早熟问题，提出了一种自适应惯性权重、异变学习因子的粒子群算法( AWSP-SO)，通过在惯性权重以及学习因子中引入粒子的局部及全局极值，平衡了粒子群算法的搜索及收敛能力。同时，将该算法应用到无线传感器网络( WSN)路由Leach协议的簇首选择问题中，利用AWSPSO算法对簇首的选择进行优化，以此均衡网络的能量消耗、延长网络生命周期。仿真结果表明，与基本Leach协议相比经过AWSPSO算法优化后的Leach协议在均匀分簇、均衡网络能量消耗以及延长网络生命周期等方面有显著改善。
Abstract:
In order to overcome the premature stagnation of Basic Particle Swarm Optimization ( BPSO ) , present an adaptive inertia weight particle swarm optimization algorithm with variation study factor. The local best and global best solution are involved in the inertia weight and the study factor to balance the exploitation and exploration ability of the particle swarm optimization. Meanwhile,the algo-rithm is applied to the election of the cluster heads in the Leach routing protocol of Wireless Sensor Networks ( WSN) to reduce the ener-gy consumptions and prolong the network life period. The simulation results show that the improved Leach protocol has more uniform clusters,reduces the energy consumptions and prolongs the network life periods than the Leach protocol.

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更新日期/Last Update: 1900-01-01