基于模拟退火算法和改进灰狼优化器的异构无线传感器网络路由协议

赵小强; 任少亚; 翟永智; 权恒; 杨婷

doi:10.11959/j.issn.2096-3750.2021.00211

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基于模拟退火算法和改进灰狼优化器的异构无线传感器网络路由协议

理论与技术 | 更新时间：2024-06-05

- 基于模拟退火算法和改进灰狼优化器的异构无线传感器网络路由协议
- Heterogeneous wireless sensor network routing protocol based on simulated annealing algorithm and modified grey wolf optimizer
- 物联网学报 2021年5卷第2期页码：97-106
- 作者机构：
  
  1. 西安邮电大学通信与信息工程学院，陕西西安 710121
  2. 陕西省信息通信网络及安全重点实验室，陕西西安 710121
- 作者简介：
  
  [ "赵小强（1977- ），男，博士，西安邮电大学教授，主要研究方向为物联网技术及应用" ]
  [ "任少亚（1994- ），女，西安邮电大学硕士生，主要研究方向为物联网技术及应用、路由协议" ]
  [ "翟永智（1976- ），男，博士，西安邮电大学讲师，主要研究方向为物联网技术及应用" ]
  [ "权恒（1994- ），男，西安邮电大学硕士生，主要研究方向为物联网技术及应用、智慧农业" ]
  [ "杨婷（1998- ），女，西安邮电大学硕士生，主要研究方向为物联网技术及应用" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(U1965102);陕西省创新人才推进计划—科技创新团队项目;The Shaanxi Innovative Talent Promotion Plan-Science and Technology Innovation Team(2019TD-28);西安市科技计划项目;The Science and Technology Projects of Xi’an(201806117YF05NC13-2);陕西省教育厅产业化培育项目;The Industrialization Cultivation Project of Shaanxi Provincial Department of Education(18JF029);陕西省国际合作计划项目;The Shaanxi International Cooperation Project(2018KW-025)
- DOI：10.11959/j.issn.2096-3750.2021.00211
  中图分类号： TP212.9；TN929.5
- 纸质出版日期：2021-06-30，
  
  网络出版日期：2021-06，
- 稿件说明：
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赵小强, 任少亚, 翟永智, 等. 基于模拟退火算法和改进灰狼优化器的异构无线传感器网络路由协议[J]. 物联网学报, 2021,5(2):97-106.

XIAOQIANG ZHAO, SHAOYA REN, YONGZHI ZHAI, et al. Heterogeneous wireless sensor network routing protocol based on simulated annealing algorithm and modified grey wolf optimizer. [J]. Chinese journal on internet of things, 2021, 5(2): 97-106.
赵小强, 任少亚, 翟永智, 等. 基于模拟退火算法和改进灰狼优化器的异构无线传感器网络路由协议[J]. 物联网学报, 2021,5(2):97-106. DOI： 10.11959/j.issn.2096-3750.2021.00211.

XIAOQIANG ZHAO, SHAOYA REN, YONGZHI ZHAI, et al. Heterogeneous wireless sensor network routing protocol based on simulated annealing algorithm and modified grey wolf optimizer. [J]. Chinese journal on internet of things, 2021, 5(2): 97-106. DOI： 10.11959/j.issn.2096-3750.2021.00211.

摘要

合理利用节点的能量异构特性延长网络生命周期是异构无线传感器网络（HWSN

heterogeneous wireless sensor network）的主要目标之一。因此，根据节点能量的异构性提出了一种基于模拟退火（SA

simulated annealing）算法和改进灰狼优化器（GWO

grey wolf optimizer）的HWSN路由协议SA-MGWO（SA-modified grey wolf optimizer）。首先，该协议通过为能量异构的节点定义不同的适应度函数进行初始簇的选取；然后计算节点的适应值，并将其视为灰狼优化器中的初始权重；同时，根据狼群与猎物的距离以及系数向量对权重进行动态更新，提高灰狼优化器的寻优能力；最后，利用模拟退火算法保证异构网络中最优簇集的选取。仿真结果表明，相比于SEP（stable election protocol）、分布式能量有效成簇（DEEC

distribute energy efficient clustering）、M-SEP及FIGWO（fitness value based improved grey wolf optimizer）协议，SA-MGWO协议的网络生命周期分别提高了53.1%、31.9%、46.5%和27.0%。

Abstract

It’s one of the main goals of the heterogeneous wireless sensor network (HWSN) to extend the network lifecycle by reasonably utilizing the heterogeneity of node energy.Therefore

according to the heterogeneity of node energy

a routing protocol (SA-MGWO) for HWSN based on simulated annealing (SA) algorithm and modified grey wolf optimizer (GWO) was proposed.Firstly

the appropriate initial clusters were selected by dening different tness functions for heterogeneous energy nodes.Secondly

The tness values of nodes were calculated and treated as initial weights in the GWO.At the same time

the weights were updated dynamically according to the distance between the wolves and their prey and coefficient vectors to improve the GWO’s optimization ability.Finally

simulated annealing algorithm was used to ensure the selection of optimal cluster set in heterogeneous networks.Compared with stable election protocol (SEP)

distribute energy efficient clustering (DEEC)

modified stable election protocol (M-SEP)

and fitness value based improved grey wolf optimizer (FIGWO) protocols

the experimental results indicate that the network lifecycle of the SA-MGWO protocol improves by 53.1%

31.9%

46.5% and 27.0% respectively.

关键词

异构无线传感器网络模拟退火算法灰狼优化器网络生命周期

Keywords

heterogeneous wireless sensor networksimulated annealing algorithmgrey wolf optimizernetwork lifecycle

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