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The MicroPulse Framework for Adaptive Waking Windows in Sensor Networks

DocUID: 2007-008 Full Text: PDF

Author: Demetrios Zeinalipour-Yazti, Panayiotis Andreou, Panos K. Chrysanthis, George Samaras, Andreas Pitsillides

Abstract: In this paper we present MicroPulse, a novel framework for adapting the waking window of a sensing device S based on the data workload incurred by a query Q. Assuming a typical tree-based aggregation scenario, the waking window is defined as the time interval  during which S enables its transceiver in order to collect the results from its children. Minimizing the length of enables S to conserve energy that can be used to prolong the longevity of the network and hence the quality of results. Our method is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the Critical Path Method. We show through tracedriven experimentation with a real dataset that MicroPulse can reduce the energy cost of the waking window by three orders of magnitude.

Published In: International Workshop on Data Intensive Sensor Networks 2007

ISBN: 1-4244-1241-2

Pages: pp. 351-355

Place Published: Mannheim, Germany

Year Published: 2007

Note: held in conjunction with MDM'07, DOI:10.1109/MDM.2007.74

Project: Others Subject Area: Sensor Databases

Publication Type: Conference Paper

Sponsor: Others, NSF ITR ANI-0325353, NSF IIS-0534531

Citation:Text Latex BibTex XML Demetrios Zeinalipour-Yazti, Panayiotis Andreou, Panos K. Chrysanthis, George Samaras, and Andreas Pitsillides. The MicroPulse Framework for Adaptive Waking Windows in Sensor Networks, International Workshop on Data Intensive Sensor Networks 2007 (DISN'07), pp. 351-355, 1-4244-1241-2 , Mannheim, Germany, May 2007.(held in conjunction with MDM'07, DOI:10.1109/MDM.2007.74)