2nd International ICST Conference on Broadband Networks

Research Article

Analysis of a prediction-based mobility adaptive tracking algorithm

  • @INPROCEEDINGS{10.1109/ICBN.2005.1589681,
        author={Jennifer Yick and Biswanath Mukherjee and Dipak Ghosal},
        title={Analysis of a prediction-based mobility adaptive tracking algorithm},
        proceedings={2nd International ICST Conference on Broadband Networks},
        publisher={IEEE},
        proceedings_a={BROADNETS},
        year={2006},
        month={2},
        keywords={},
        doi={10.1109/ICBN.2005.1589681}
    }
    
  • Jennifer Yick
    Biswanath Mukherjee
    Dipak Ghosal
    Year: 2006
    Analysis of a prediction-based mobility adaptive tracking algorithm
    BROADNETS
    IEEE
    DOI: 10.1109/ICBN.2005.1589681
Jennifer Yick1,*, Biswanath Mukherjee1,*, Dipak Ghosal1,*
  • 1: Department of Computer Science, University of California Davis
*Contact email: yick@cs.ucdavis.edu , mukherje@cs.ucdavis.edu, ghosal@cs.ucdavis.edu

Abstract

Target tracking in wireless sensor networks requires efficient coordination among sensor nodes. Existing methods have focused on tree-based collaboration, selective activation, and group clustering. This paper presents a prediction-based adaptive algorithm for tracking mobile targets. We use adaptive Kalman filtering to predict the future location and velocity of the target. This location prediction is used to determine the active tracking region which corresponds to the set of sensors that needs to be "lighted". The velocity prediction is used to adaptively determine the size of the active tracking region, and to modulate the sampling rate as well. In this paper, we quantify the benefits of our approach in terms of energy consumed and accuracy of tracking for different mobility patterns. Our simulation results show that advance resource reservation coupled with adaptively changing the size of the active tracking region and the sampling rate reduces the overall energy consumed for tracking without affecting the accuracy in tracking.