Two-Stage Localization Algorithm Based on Greedy Idea for Wireless Sensor Networks

MENG Ying-hui; CHEN Jian; WEN Ying-you; ZHAO Hong

您当前的位置：

首页 >

文章列表页 >

Two-Stage Localization Algorithm Based on Greedy Idea for Wireless Sensor Networks

更新时间：2025-07-16

- Two-Stage Localization Algorithm Based on Greedy Idea for Wireless Sensor Networks
- Acta Electronica Sinica Vol. 42, Issue 2, Pages: 328-334(2014)
- 作者机构：
  
  东北大学信息科学与工程学院,辽宁,沈阳,110819
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.60903159, No.61173153);Fundamental Research Funds for the Central Universities (No.110818001, No.100218001, No.110404014, No.110318001);Shenyang Science and Technology Plan Project (No.1091176-1-00);China Postdoctoral Science Foundation (No.20110491508, No.2012T50248)
- DOI：
  CLC： TP393
- Published：2014
- 稿件说明：
移动端阅览
MENG Ying-hui, CHEN Jian, WEN Ying-you, et al. Two-Stage Localization Algorithm Based on Greedy Idea for Wireless Sensor Networks[J]. Acta Electronica Sinica, 2014, 42(2): 328-334.
DOI：

MENG Ying-hui, CHEN Jian, WEN Ying-you, et al. Two-Stage Localization Algorithm Based on Greedy Idea for Wireless Sensor Networks[J]. Acta Electronica Sinica, 2014, 42(2): 328-334. DOI：

摘要

近些年来，将优化算法应用到节点定位问题当中成为了一个研究热点.本文假设下一次定位结果为准确坐标，对前后两次定位结果邻居节点之间距离关系进行深度分析和推导，得到一个邻域函数.在此基础上根据贪婪思想，提出了贪婪定位算法.为了达到更精确的定位结果，本文将贪婪定位算法分成两个阶段：第一阶段，根据贪婪迭代优化得到一组初始定位结果；第二阶段将满足一定条件的未知节点升级为锚节点，重新执行第一阶段的过程，重复第二阶段，直到没有未知节点可以升级为锚节点为止.实验结果表明，无论是定位精确度还是算法执行时间，本文所提算法都比当前的一些优化定位算法要好.

Abstract

Using optimization algorithm to solve the node localization problem has become a research focus.This paper makes deep analysis on the distance relationship between two successive localization results and designs a neighborhood function

and then proposes the greedy localization algorithm based on greedy idea.The proposed algorithm is divided into two phases.In the first phase

a set of estimated positions is generated based on the greedy iterative optimization.In the second phase

some unknown nodes will be elevated to anchor nodes

and the first phase is executed again.The second phase is repeated until there is no node that can be elevated to an anchor node.Finally

the experimental results show the proposed algorithm achieves more accurate result and take less time than the existing optimization localization algorithms.

关键词

Keywords

references

Views

1359

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Federated Learning Scheme for Environmental Monitoring Based on Edge Computing

MAP-Based Multi-Information Flow Gradient Update and Aggregation for Video Compressed Sensing Reconstruction

Estimation Method of Wireless Link Quality and Routing Optimization Algorithm Based on Correlation Transmission Model

Speed Regulation of Scale Adjustment in Quantum-Inspired Optimization Algorithm

Related Author

JIANG Wei-jin

HAN Yu-qing

WANG Hai-juan

CHEN Yi-lin

WU Yu-ting

ZHOU Wei

YANG Xin

YANG Chun-ling

Related Institution

College of Frontier Intersection， Hunan University of Technology and Business

Xiangjiang Laboratory

School of Computer Science and Artificial Intelligence， Wuhan University of Technology

School of Computer Science， Hunan University of Technology and Business

School of Electronic and Information Engineering， South China University of Technology

⁰