Tracking Nodes Selection Algorithm Based on Voronoi Structure in Sensor Networks
Author:
Affiliation:

  • Article
  • | |
  • Metrics
  • |
  • Reference [14]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    Energy saving and the tracking performance are two important issues in moving target tracking. This paper presents a Voronoi structure-based nodes selection algorithm, which constructs a network model based on the property of Voronoi, and selects sensor nodes which are more close to the target to participate in tracking. This paper also presents a nodes scheduling mechanism, which minimizes the number of awaking nodes with tracking quality guarantee. Finally, a set of simulation experiments are made to analyze the effects of various parameters on the network performance. Experimental results show the excellent performance of the proposed algorithm in terms of energy saving and tracking quality.

    Reference
    [1] Souza M, Wark T, Karunanithi M, Ros M. Evaluation of realtime people tracking for indoor environments using ubiquitous motion sensors and limited wireless network infrastructure. Pervasive & Mobile Computing, 2013,9(4):498-515.
    [2] Ren QQ, Li JZ. Information quality-aware tracking in uncertain sensor network. IJSNET, 2013,14(1):33-40.
    [3] Cheng SY, Li JZ, Ren QQ, Yu L. Bernoulli sampling based (ε,δ)-approximate aggregation in large-scale sensor networks. In:Proc. of the INFOCOM Congress. 2010. 1181-1189.
    [4] Fang XL, Gao H, Li JZ, Li YS. Application-Aware data collection in wireless sensor networks. In:Proc. of the INFOCOM Congress. 2013. 1645-1653.
    [5] Zhang B, Tong ED, Hao J, Niu WJ, Li G. Energy efficient sleep schedule with service coverage guarantee in wireless sensor networks. Journal of Network & Systems Management, 2016,24(2016):834-858.
    [6] Feng J, Lian BW, Zhao HW. Adaptive energy optimization for object tracking in wireless sensor network. KSⅡ Trans. on Internet and Information Systems, 2015,9(4):1359-1375.
    [7] Mantri DS, Pawar PM, Prasad NR, Prasad R. An efficient schedule based data aggregation using node mobility for wireless sensor network. In:Proc. of the VITAE Congress. 2014. 1-5.
    [8] Sherly PAL, Murugan K. An energy efficient wakeup schedule and power management algorithm for wireless sensor networks. In:Proc. of the ICRTIT Congress. 2012. 314-319.
    [9] Zhao W, Han Y, Wu H, Zhang L. Weighted distance based sensor selection for target tracking in wireless sensor networks. IEEE Signal Processing Letters, 2009,16(8):647-650.
    [10] Li D, Wong KD, Hu YH, Sayeed A. Detection, classification and tracking of targets in distributed sensor networks. IEEE Signal Processing Magazine, 2002,19(2):17-29.
    [11] Yang XS, Zhang WA, Chen ZQ, Yu L. Hybrid sequential fusion estimation for asynchronous sensor network-based target tracking. IEEE Trans. on Control Systems Technology, 2017,25(2):669-676.
    [12] Zhong ZG, Zhu T, Wang D, He T. Tracking with unreliable node sequences. In:Proc. of the INFOCOM Congress. 2009. 1215-1223.
    [13] Ding M, Cheng XZ. Fault tolerant target tracking in sensor networks. In:Proc. of the MOBIHOC. 2009. 125-134.
    [14] Handy MJ, Haase M, Timmermann D. Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In:Proc. of the MWCN. 2002. 368-372.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

任倩倩,李金宝,孙蓓蓓.传感器网络中一种基于维诺图的跟踪节点选择算法.软件学报,2017,28(s1):30-38

Copy
Share
Article Metrics
  • Abstract:1888
  • PDF: 3417
  • HTML: 0
  • Cited by: 0
History
  • Received:May 15,2017
  • Online: December 15,2017
You are the first2033335Visitors
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