# [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] 点击复制 WSN中基于梯度和粒子群优化算法的分级簇算法() 分享到： var jiathis_config = { data_track_clickback: true };

37卷

2016年02期

33-36

2016-04-18

## 文章信息/Info

Title:
Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN

Author(s):
Yan Xinfang; Yan Jingjing; Feng Yan
School of Information Engineering, Zhengzhou University, Zhengzhou, Henan 450001

Keywords:
DOI:
10.3969/j.issn.1671-6833.201505017

A

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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