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Minimizing energy consumptions in wireless sensor networks via two-modal transmission

Published: 07 January 2010 Publication History

Abstract

We present a sophisticated framework to systematically explore the temporal correlation in environmental monitoring wireless sensor networks. The presented framework optimizes lossless data compression in communications given the resource constraint of sensor nodes. The insights and analyses obtained from the framework can directly lead to innovative and better design of data gathering protocols for wireless sensor networks operated in noisy environments to dramatically reduce the energy consumptions.

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Cited By

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  • (2022)Edge Computing of Online Bounded-Error Query for Energy-Efficient IoT SensorsSensors10.3390/s2213479922:13(4799)Online publication date: 24-Jun-2022
  • (2022)A Fuzzy Logic based Offloading System for Distributed Deep Learning in Wireless Sensor Networks2022 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN55064.2022.9892817(1-8)Online publication date: 18-Jul-2022
  • (2021)Video-Like Lossless Compression of Data Cube for Big Data Query in Wireless Sensor NetworksWSEAS TRANSACTIONS ON COMMUNICATIONS10.37394/23204.2021.20.1920(139-145)Online publication date: 10-Aug-2021
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        Published In

        cover image ACM SIGCOMM Computer Communication Review
        ACM SIGCOMM Computer Communication Review  Volume 40, Issue 1
        January 2010
        128 pages
        ISSN:0146-4833
        DOI:10.1145/1672308
        Issue’s Table of Contents

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 07 January 2010
        Published in SIGCOMM-CCR Volume 40, Issue 1

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        Author Tags

        1. energy efficiency
        2. lossless compression
        3. wireless sensor networks

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        • (2022)Edge Computing of Online Bounded-Error Query for Energy-Efficient IoT SensorsSensors10.3390/s2213479922:13(4799)Online publication date: 24-Jun-2022
        • (2022)A Fuzzy Logic based Offloading System for Distributed Deep Learning in Wireless Sensor Networks2022 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN55064.2022.9892817(1-8)Online publication date: 18-Jul-2022
        • (2021)Video-Like Lossless Compression of Data Cube for Big Data Query in Wireless Sensor NetworksWSEAS TRANSACTIONS ON COMMUNICATIONS10.37394/23204.2021.20.1920(139-145)Online publication date: 10-Aug-2021
        • (2021)Novel Data Compression Algorithm for Transmission Line Condition MonitoringEnergies10.3390/en1424827514:24(8275)Online publication date: 8-Dec-2021
        • (2021)Compressing the Index on Distributed Data of SensorsIEEE Sensors Journal10.1109/JSEN.2021.306619921:10(12313-12321)Online publication date: 15-May-2021
        • (2021)Data Compression Algorithms for Wireless Sensor Networks: A Review and ComparisonIEEE Access10.1109/ACCESS.2021.31163119(136872-136891)Online publication date: 2021
        • (2021)Blockchain for bounded-error-pruned content protectionICT Express10.1016/j.icte.2021.08.013Online publication date: Aug-2021
        • (2021)Data Traffic Management Based on Compression and MDL Techniques for Smart Agriculture in IoTWireless Personal Communications: An International Journal10.1007/s11277-021-08563-4120:3(2227-2258)Online publication date: 1-Oct-2021
        • (2021)Information-Based Node Selection for Joint PCA and Compressive Sensing-Based Data Aggregation Wireless Personal Communications: An International Journal10.1007/s11277-021-08108-9118:2(1635-1654)Online publication date: 1-May-2021
        • (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
        • Show More Cited By

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