基于局域信息和能量因素的WSN关键点判定算法

刘彬; 孙雅静; 刘浩然; 尹荣荣

doi:10.11959/j.issn.1000-436x.2015216

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基于局域信息和能量因素的WSN关键点判定算法

学术论文 | 更新时间：2024-06-05

- 基于局域信息和能量因素的WSN关键点判定算法
- Key node decision algorithm based on local information and energy factor in wireless sensor network
- 通信学报 2015年36卷第10期页码：9-16
- 作者机构：
  
  1. 燕山大学电气工程学院，河北秦皇岛 066004
  2. 燕山大学河北省特种光纤与光纤传感重点实验室，河北秦皇岛 066004
- 作者简介：
  
  [ "刘彬（1953-），男，黑龙江五常人，燕山大学教授、博士生导师，主要研究方向为信号估计与识别、轧机扭振动力行为及测量技术、智能传感及无线传感器网络关键技术、智能控制技术及在水泥生产中的应用等。" ]
  [ "孙雅静（1991-），女，河北承德人，燕山大学硕士生，主要研究方向为无线传感器网络容错拓扑建模及网络性能分析。" ]
  [ "刘浩然（1980-），男，黑龙江五常人，燕山大学副教授、硕士生导师，主要研究方向为无线传感器网络拓扑控制、工业故障检测等。" ]
  [ "尹荣荣（1985-），女，甘肃白银人，燕山大学讲师，主要研究方向为无线传感器网络拓扑容错性分析及控制。" ]
- 基金信息：
  
  河北省自然科学基金资助项目(F2014203239);河北省自然科学基金资助项目(F2015203091)
- DOI：10.11959/j.issn.1000-436x.2015216
  中图分类号： TP393
- 网络出版日期：2015-10，
  
  纸质出版日期：2015-10-25
- 稿件说明：
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刘彬, 孙雅静, 刘浩然, 等. 基于局域信息和能量因素的WSN关键点判定算法[J]. 通信学报, 2015,36(10):9-16.

Bin LIU, Ya-jing SUN, Hao-ran LIU, et al. Key node decision algorithm based on local information and energy factor in wireless sensor network[J]. Journal on communications, 2015, 36(10): 9-16.
刘彬, 孙雅静, 刘浩然, 等. 基于局域信息和能量因素的WSN关键点判定算法[J]. 通信学报, 2015,36(10):9-16. DOI： 10.11959/j.issn.1000-436x.2015216.

Bin LIU, Ya-jing SUN, Hao-ran LIU, et al. Key node decision algorithm based on local information and energy factor in wireless sensor network[J]. Journal on communications, 2015, 36(10): 9-16. DOI： 10.11959/j.issn.1000-436x.2015216.

摘要

针对无线传感器网络现有关键点判定方法中，判定指标比较单一，容易导致关键点判定结果不全面的问题，综合考虑节点局域信息和能量因素，提出一种新的关键点判定算法。此算法首先利用节点自身度与其邻居信息对节点局域信息进行建模，接下来结合节点剩余能量和节点失效后网络能耗的变化，建立能量因素模型，最终得到一个综合的关键点判定模型。利用Matlab仿真平台与其他算法进行对比仿真，结果表明该算法能使关键点判定更加全面，同时验证在保护由此算法判定所得关键点时，网络能够表现出强抗毁性，验证此算法的有效性。

Abstract

In the existing key node decision methods for wireless sensor network

the judgment index was so single that the result judged was deficient.In order to solve this problem

a new key node decision algorithm(KNDA)based on local information and energy factor was proposed.Firstly

the local information model based on the degree and neighbor information of node was established.Secondly

according to the residual energy of node and the change of network energy consumption after the node failed

the models of energy factors were established.Finally

an aggregative key node decision model was formed.Extensive simulation experiments were carried out in the MATLAB simulation platform

by comparing with other algorithms

the results verify that the key nodes obtained by this algorithm are more sufficient.Meanwhile when the key nodes judged by KNDA are protected

the network can show strong invulnerability.

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