WSN中基于改进粒子群优化算法的分簇路由协议

doi:10.11959/j.issn.1000-436x.2019241

通信学报 ›› 2019, Vol. 40 ›› Issue (12): 114-123.doi: 10.11959/j.issn.1000-436x.2019241

WSN中基于改进粒子群优化算法的分簇路由协议

武小年¹,张楚芸¹,张润莲^1,²,孙亚平¹

¹ 桂林电子科技大学广西密码学与信息安全重点实验室，广西桂林 541004
² 桂林电子科技大学广西高校云计算与复杂系统重点实验室，广西桂林 541004

修回日期:2019-11-15 出版日期:2019-12-25 发布日期:2020-01-16
作者简介:武小年（1972– ），男，湖北监利人，桂林电子科技大学副教授，主要研究方向为分布式计算和信息安全|张楚芸（1993– ），女，广西贺州人，桂林电子科技大学硕士生，主要研究方向为无线传感器网络。|张润莲（1974– ），女，山西介休人，博士，桂林电子科技大学副教授，主要研究方向为分布式计算和信息安全。|孙亚平（1993– ），女，山东菏泽人，桂林电子科技大学硕士生，主要研究方向为信息安全。
基金资助:
广西自然科学基金资助项目(2018GXNSFAA294036);广西自然科学基金资助项目(2018GXNSFAA138116);广西密码学与信息安全重点实验室基金资助项目(GCIS201705);广西密码学与信息安全重点实验室基金资助项目(GCIS201623);广西高校云计算与复杂系统重点实验室基金资助项目(YF16205);广西研究生教育创新计划基金资助项目(YCSW2018138);广西研究生教育创新计划基金资助项目(2017YJCX26)

Clustering routing protocol based on improved PSO algorithm in WSN

Xiaonian WU¹,Chuyun ZHANG¹,Runlian ZHANG^1,²,Yaping SUN¹

¹ Guangxi Key Laboratory of Cryptography and Information Security,Guilin University of Electronic Technology,Guilin 541004,China
² Guangxi Colleges Key Laboratory of Cloud Computing and Complex Systems,Guilin University of Electronic Technology,Guilin 541004,China

Revised:2019-11-15 Online:2019-12-25 Published:2020-01-16
Supported by:
The Natural Science Foundation of Guangxi Province(2018GXNSFAA294036);The Natural Science Foundation of Guangxi Province(2018GXNSFAA138116);Guangxi Key Laboratory of Cryptography and Information Security(GCIS201705);Guangxi Key Laboratory of Cryptography and Information Security(GCIS201623);Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems(YF16205);nnovation Project of Guangxi Graduate Education(YCSW2018138);nnovation Project of Guangxi Graduate Education(2017YJCX26)

摘要/Abstract

摘要：

针对无线传感器网络分簇路由协议所筛选簇头节点的位置分布不均衡及转发节点的数据传输路径不合理会加剧节点能量消耗、缩短网络生存周期的问题，提出一种基于改进粒子群优化算法的分簇路由协议。在簇头选举过程中，通过定义节点的能量因子和位置均衡因子建立新的适应度函数，评估和选择更优的候选簇头节点；通过优化的自适应学习因子调整候选簇头节点的位置更新速度，扩大局部搜索并加快全局搜索的收敛速度。根据转发节点与基站的距离确定采用单跳还是多跳传输方式，设计一种基于最小生成树的多跳方法，为转发节点数据传输选择最优的多跳路径。仿真测试结果表明，基于改进粒子群算法的分簇路由协议能够选举能量与位置更均衡的簇头节点和转发节点，缩短了网络的通信距离，节点的能耗更低且更均衡，有效延长了网络生存周期。

关键词: 无线传感器网络, 粒子群优化算法, 分簇协议, 多跳, 最小生成树

Abstract:

Aiming at the problem that the location distribution of cluster head nodes filtered by wireless sensor network clustering routing protocol was unbalanced and the data transmission path of forwarding nodes was unreasonable,which would increase the energy consumption of nodes and shorten the network life cycle,a clustering routing protocol based on improved particle swarm optimization algorithm was proposed.In the process of cluster head election,a new fitness function was established by defining the energy factor and position equalization factor of the node,the better candidate cluster head node was evaluated and selected,the position update speed of the candidate cluster head nodes was adjusted by the optimized update learning factor,the local search and speeded up the convergence of the global search was expanded.According to the distance between the forwarding node and the base station,the single-hop or multi-hop transmission mode was adopted,and a multi-hop method was designed based on the minimum spanning tree to select an optimal multi-hop path for the data transmission of the forwarding node.Simulation results show that the clustering routing protocol based on improved particle swarm optimization algorithm can elect cluster head nodes and forwarding nodes with more balanced energy and location,which shortened the communication distance of the network.The energy consumption of nodes is lower and more balanced,effectively extending the network life cycle.

Key words: wireless sensor network, particle swarm optimization algorithm, clustering protocol, multi-hop, minimum spanning tree

中图分类号:

TP393

武小年,张楚芸,张润莲,孙亚平. WSN中基于改进粒子群优化算法的分簇路由协议[J]. 通信学报, 2019, 40(12): 114-123.

Xiaonian WU,Chuyun ZHANG,Runlian ZHANG,Yaping SUN. Clustering routing protocol based on improved PSO algorithm in WSN[J]. Journal on Communications, 2019, 40(12): 114-123.

图/表 7

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参数名称	取值
节点数目	100
基站位置	(50,175)
网络规模	100 m × 100 m
最大轮数r_max	2 500
算法迭代次数	100
最优簇数量	5
粒子个数	20
数据分组长度/bit	4 000
控制分组长度/bit	200
节点初始能量E₀/J	0.5
E_fs/(pJ.(bit?m²)^–1)	10
E_mp/(pJ.(bit?m⁴)^–1)	0.001 3
E_elec/(nJ.bit^–1)	50
d₀/m	87

WSN中基于改进粒子群优化算法的分簇路由协议

Clustering routing protocol based on improved PSO algorithm in WSN

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