Earticle

초록

영어

In this paper, a novel approach to multi-hop range-free localization algorithm in wireless sensor network is proposed using principal component regression. The localization problem in the wireless sensor network is formulated as a multiple regression problem, which is resolved by principal component regression. The proposed methods are simple and efficient that no additional hardware is required for the measurements, and only hop-counts information and location information of the beacons are used for the localization. The proposed method consists of two phases: the offline training phase and the online localization phase. In offline training phase, the real distances and the hop-counts among sensor nodes are collected to build localization model. In online localization phase, each unknown sensor node finds its own location using the localization model. The experimental results show that compared with previous localization methods, the proposed method exhibits excellent and robust performances not only in the isotropic sensor networks but also in the anisotropic sensor networks.

목차

Abstract
 1. Introduction
 2. Background
 3. Sensor Node Location Estimation
  3.1. Problem Statement
  3.2. Localization Algorithm
 4. Performance Evaluation
  4.1 Simulation Setting
  4.2 Regularly Deployed Sensors
  4.3 Random Deployed Sensors
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Xianghong Tian [ School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169, China ]
• Wei Zhao [ School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169, China ]
• Xiaoyong Yan [ School of Intelligence Science and Control, Jinling Institute of Technology, Nanjing 211169, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605