Prediction-based strategies for energy saving in object tracking sensor networks

Yingqi Xu, Julian Winter, Wang Chien Lee

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

226 Scopus citations

Abstract

In order to fully realize the potential of sensor networks, energy awareness should be incorporated into every stage of the network design and operation. In this paper, we address the energy management issue in a sensor network killer application - object tracking sensor networks (OTSNs). Based on the fact that the movements of the tracked objects are sometimes predictable, we propose a Prediction-based Energy Saving scheme, called PES, to reduce the energy consumption for object tracking under acceptable conditions. We compare PES against the basic schemes we proposed in the paper to explore the conditions under which PES is most desired. We also test the effect of some parameters related to the system workload, object moving behavior and sensing operations on PES through extensive simulation. Our results show that PES can save significant energy under various conditions.

Original languageEnglish (US)
Title of host publicationProceedings - 2004 IEEE International Conference on Mobile Data Management (MDM 2004)
Pages346-357
Number of pages12
StatePublished - 2004
EventProceedings - 2004 IEEE International Conference on Mobile Data Management, MDM 2004 - Berkeley, CA., United States
Duration: Jan 19 2004Jan 22 2004

Publication series

NameProceedings - 2004 IEEE International Conference on Mobile Data Management

Other

OtherProceedings - 2004 IEEE International Conference on Mobile Data Management, MDM 2004
CountryUnited States
CityBerkeley, CA.
Period1/19/041/22/04

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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