Neighbor Discovery Algorithm in Mobile Low Duty Cycle WSNs
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Low duty cycle is proposed to reduce the energy consumption of WSNs (wireless sensor networks), thereby extending the lifecycle of WSNs. However, low duty cycle makes neighbor discovery extremely difficult. Especially considering the mobility of nodes, effective neighbor discovery is more challenging. In this work, a new neighbor discovery algorithm based on Continuous Torus Quorum is proposed to solve the neighbor discovery problem in asynchronous symmetric and asymmetric low duty cycle WSNs. A neighbor discovery probability is also provided to estimate efficiency of neighbor discovery algorithms in mobile scene. Furthermore, a simulation platform is developed to measure performance of neighbor discovery algorithms. Both theoretical analysis and simulation results reveal that Continuous-Torus-Quorum-based algorithm can achieve significant performance improvement over several classical heterogeneous neighbor discovery algorithms, such as Disco and U-Connect, in terms of energy efficiency, discovery delay and discovery probability in the symmetric and asymmetric scenes.

    Reference
    Related
    Cited by
Get Citation

陈良银,颜秉姝,张靖宇,胡剑波,刘振磊,刘燕,徐正坤,罗谦.移动低占空比传感网邻居发现算法.软件学报,2014,25(6):1352-1368

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:January 13,2012
  • Revised:November 14,2012
  • Adopted:
  • Online: May 30,2014
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063