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Prediction-based monitoring in sensor networks: taking lessons from MPEG

Authors:

Tomasz ImielinskiAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 31, Issue 5

Pages 82 - 98

https://doi.org/10.1145/1037107.1037117

Published: 01 October 2001 Publication History

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.

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Cited By

Chakraborty AGovindarajan CGovindarajan KNaik PGoel S(2024)Enabling Programmable Metric Flows2024 IEEE 17th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD62652.2024.00050(386-398)Online publication date: 7-Jul-2024
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Sharma VZubair Khan MBatra SAlsaeedi ASrivastava P(2023)Optimizing Storage for Energy Conservation in Tracking Wireless Sensor Network ObjectsComputer Systems Science and Engineering10.32604/csse.2023.02918445:2(1211-1231)Online publication date: 2023
https://doi.org/10.32604/csse.2023.029184
Kavitha AGuravaiah KLeela Velusamy RSuseela SKumar D(2023)DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networksInternational Journal of Communication Systems10.1002/dac.546736:8Online publication date: 14-Mar-2023
https://doi.org/10.1002/dac.5467
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Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 31, Issue 5

Special issue on wireless extensions to the internet

October 2001

92 pages

ISSN:0146-4833

DOI:10.1145/1037107

Issue’s Table of Contents

Copyright © 2001 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 October 2001

Published in SIGCOMM-CCR Volume 31, Issue 5

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Cited By

Chakraborty AGovindarajan CGovindarajan KNaik PGoel S(2024)Enabling Programmable Metric Flows2024 IEEE 17th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD62652.2024.00050(386-398)Online publication date: 7-Jul-2024
https://doi.org/10.1109/CLOUD62652.2024.00050
Sharma VZubair Khan MBatra SAlsaeedi ASrivastava P(2023)Optimizing Storage for Energy Conservation in Tracking Wireless Sensor Network ObjectsComputer Systems Science and Engineering10.32604/csse.2023.02918445:2(1211-1231)Online publication date: 2023
https://doi.org/10.32604/csse.2023.029184
Kavitha AGuravaiah KLeela Velusamy RSuseela SKumar D(2023)DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networksInternational Journal of Communication Systems10.1002/dac.546736:8Online publication date: 14-Mar-2023
https://doi.org/10.1002/dac.5467
Engmann FSarpong Adu-Manu KAbdulai JApietu Katsriku F(2021)Applications of Prediction Approaches in Wireless Sensor NetworksWireless Sensor Networks - Design, Deployment and Applications10.5772/intechopen.94500Online publication date: 15-Sep-2021
https://doi.org/10.5772/intechopen.94500
Yassin-Kassab HMarius-Corneliu Rosu (2021)An Overview of Own Tracking Wireless Sensors with GSM-GPS FeaturesAdvances in Technology Innovation10.46604/aiti.2021.47936:1(47-66)Online publication date: 1-Jan-2021
https://doi.org/10.46604/aiti.2021.4793
Wang YYang KWan WZhang YLiu Q(2021)Energy-Efficient Data and Energy Integrated Management Strategy for IoT Devices Based on RF Energy HarvestingIEEE Internet of Things Journal10.1109/JIOT.2021.30680408:17(13640-13651)Online publication date: 1-Sep-2021
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Wang YYang KWan WMei H(2021)Adaptive energy saving algorithms for Internet of Things devices integrating end and edge strategiesTransactions on Emerging Telecommunications Technologies10.1002/ett.412232:8Online publication date: 6-Aug-2021
https://dl.acm.org/doi/10.1002/ett.4122
Chang RChu YWei LWang C(2020)Bounded-Error-Pruned Sensor Data Compression for Energy-Efficient IoT of Environmental IntelligenceApplied Sciences10.3390/app1018651210:18(6512)Online publication date: 18-Sep-2020
https://doi.org/10.3390/app10186512
Rashid MKamruzzaman JHassan MShahriar Shafin SBhuiyan M(2020)A Survey on Behavioral Pattern Mining From Sensor Data in Internet of ThingsIEEE Access10.1109/ACCESS.2020.29740358(33318-33341)Online publication date: 2020
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Mejia JOchoa-Zezzatti ACruz-Mejía OMederos B(2020)Prediction of time series using wavelet Gaussian process for wireless sensor networksWireless Networks10.1007/s11276-020-02250-126:8(5751-5758)Online publication date: 1-Nov-2020
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