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ABSTRACT
In this paper we discuss the problem of monitoring data sensed in large sensor networks. A sensor typically runs on a battery having a limited lifetime. In order to increase the lifetime of a sensor it is important that the mechanisms used in monitoring them be energy-efficient. In this paper, we propose a new paradigm called Prediction-based monitoring for energy-efficient monitoring. We show that the paradigm can be visualized as a watching of a "sensor movie" and that concepts from MPEG may be applied to it. We have implemented the proposed algorithms in a test bed of Rene Motes [2]. Experimental results show that the proposed solutions cut down the energy consumption by more than 5 times, considerably increasing sensor lifetimes, and thereby, the lifetime of the networks formed from these sensors.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 23
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Mohamed A. Sharaf , Jonathan Beaver , Alexandros Labrinidis , Panos K. Chrysanthis, TiNA: a scheme for temporal coherency-aware in-network aggregation, Proceedings of the 3rd ACM international workshop on Data engineering for wireless and mobile access, September 19-19, 2003, San Diego, CA, USA
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Sergio Ilarri , Ouri Wolfson , Eduardo Mena , Arantza Illarramendi , Prasad Sistla, A query processor for prediction-based monitoring of data streams, Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, March 24-26, 2009, Saint Petersburg, Russia
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