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10429 Energy-Efficient Data Acquisition using a Distributed and Self-organizing Scheduling Algorithm for Wireless Sensor Networks
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Chatterjea, S. and Nieberg, T. and Zhang, Yang and Havinga, P.J.M. (2007) Energy-Efficient Data Acquisition using a Distributed and Self-organizing Scheduling Algorithm for Wireless Sensor Networks. In: Proceedings of the Third IEEE Conference on Distributed Computing in Sensor Systems, DCOSS 2007, 18-20 Jun 2007, Santa Fe, USA. pp. 368-385. Lecture Notes in Computer Science 4549 (LNCS4549). Springer Verlag. ISSN 0302-9743 ISBN 978-3-540-73089-7

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Official URL: http://dx.doi.org/10.1007/978-3-540-73090-3_25

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Abstract

Wireless sensor networks (WSNs) are often densely deployed for environmental monitoring applications. Collecting raw data from these networks presents problems, e.g. batteries drain out rapidly due to large amounts of data transmission and poor quality of data results from dropped packets due to limited bandwidth of present day sensor nodes. We present a novel solution to alleviate this problem. Using the spatial and temporal correlations that exist between adjacent nodes we appoint a few as representative nodes that perform in-network aggregation, thus reducing the total number of transmissions. Our distributed scheduling algorithm autonomously assigns a particular node to perform aggregation and reassigns schedules when network topology changes. These topology changes are detected using cross-layer information from the underlying MAC layer. We also present theoretical performance estimates and upper bounds of our algorithm and evaluate it by implementing the algorithm on actual sensor nodes, demonstrating an energy-saving of up to 80% compared to raw data collection.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-CAES: Computer Architecture for Embedded Systems
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:e-SENSE: Capturing Ambient Intelligence for Mobile Communications through Wireless Sensor Networks
Additional Information:Please do not refer to the paper on the Springer website as there are some major printing errors in the figures. Please download the paper directly from e-Prints instead.
Uncontrolled Keywords:data aggregation, distributed scheduling, sensor networks
ID Code:10429
Status:Published
Deposited On:21 September 2007
Refereed:Yes
International:Yes
More Information:statisticsmetis

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