Adaptive tracking in distributed wireless sensor networks

Lizhi Yang, Chuan Feng, Jerzy W. Rozenblit, Haiyan Qiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

45 Scopus citations

Abstract

We study the problem of tracking moving objects using distributed Wireless Sensor Networks (WSNs) in which sensors are deployed randomly. Due to the uncertainty and unpredictability of real-world objects' motion, the tracking algorithm is needed to adapt to real-time changes of velocities and directions of a moving target. Moreover, the energy consumption of the tracking algorithm has to be considered because of the inherent limitations of wireless sensors. In this paper, we proposed an energy efficient tracking algorithm, called Predict-and-Mesh (PaM) that is well suited for pervasively monitoring various kinds of objects with random movement patterns. PaM is a distributed algorithm consisting of two prediction models: n-step prediction and collaborative prediction, and a predication failure recovery process called mesh. The simulation results show that the PaM algorithm is robust against diverse motion changes and has the excellent performance.

Original languageEnglish (US)
Title of host publicationProceedings - 13th Annual IEEE International Symposium and Workshop on Engineering of Computer Based Systems, ECBS 2006
Pages103-111
Number of pages9
DOIs
StatePublished - 2006
Event13th Annual IEEE International Symposium and Workshop on Engineering of Computer-Based Systems, ECBS 2006 - Potsdam, Germany
Duration: Mar 27 2006Mar 30 2006

Publication series

NameProceedings of the International Symposium and Workshop on Engineering of Computer Based Systems

Other

Other13th Annual IEEE International Symposium and Workshop on Engineering of Computer-Based Systems, ECBS 2006
Country/TerritoryGermany
CityPotsdam
Period3/27/063/30/06

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software

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