[1]严晶晶,阎新芳,冯岩.WSN中基于梯度和粒子群优化算法的分级簇算法[J].郑州大学学报(工学版),2016,37(02):33-36.[doi:10.3969/j.issn.1671-6833.201505017]
　Yan Xinfang,Yan Jingjing,Feng Yan.Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN[J].Journal of Zhengzhou University (Engineering Science),2016,37(02):33-36.[doi:10.3969/j.issn.1671-6833.201505017]
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WSN中基于梯度和粒子群优化算法的分级簇算法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
37
期数:
2016年02期
页码:
33-36
栏目:
出版日期:
2016-04-18

文章信息/Info

Title:
Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN
作者:
严晶晶; 阎新芳; 冯岩
郑州大学信息工程学院,河南郑州,450001
Author(s):
Yan Xinfang; Yan Jingjing; Feng Yan
School of Information Engineering, Zhengzhou University, Zhengzhou, Henan 450001
关键词:
无线传感器网络; 梯度; 粒子群算法; GPHCA; 双簇头
Keywords:
wireless sensor networks;  gradient;  particle swarm optimization;  GPHCA;  double cluster heads
DOI:
10.3969/j.issn.1671-6833.201505017
文献标志码:
A
摘要:
为均衡网络中节点的能量消耗,提出一种分级簇算法——GPHCA.该算法采用双簇头模式,利用粒子群优化算法搜寻能量大且到簇成员平均距离小的两个节点作为主簇头和副簇头,将簇头负担均衡到了两个节点上;在网关的选择上,同时考虑能量和转发路径的总距离,使最终选择的网关在能量和时延上得到均衡.仿真结果表明,GPHCA算法能有效延长网络的生命周期.
Abstract:
In order to balance the energy consumption of nodes in the network, a hierarchical clustering algorithm—GPHCA is proposed. This algorithm adopts the dual cluster head mode, and uses the particle swarm optimization algorithm to search for two nodes with large energy and small average distance to cluster members as the main cluster head. and the sub-cluster head to balance the burden of the cluster head on the two nodes; in the selection of the gateway, the energy and the total distance of the forwarding path are considered at the same time, so that the final selected gateway can be balanced in terms of energy and delay. The simulation results show that, The GPHCA algorithm can effectively prolong the life cycle of the network.

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