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International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 286981, 17 pages
Research Article

Adaptive WSN Scheduling for Lifetime Extension in Environmental Monitoring Applications

UCD Complex and Adaptive Systems Laboratory, UCD School of Computer Science and Informatics, University College Dublin, Ireland

Received 15 June 2011; Accepted 27 August 2011

Academic Editor: Yuhang Yang

Copyright © 2012 Jong Chern Lim and Chris Bleakley. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Wireless sensor networks (WSNs) are often used for environmental monitoring applications in which nodes periodically measure environmental conditions and immediately send the measurements back to the sink for processing. Since WSN nodes are typically battery powered, network lifetime is a major concern. A key research problem is how to determine the data gathering schedule that will maximize network lifetime while meeting the user's application-specific accuracy requirements. In this work, a novel algorithm for determining efficient sampling schedules for data gathering WSNs is proposed. The algorithm differs from previous work in that it dynamically adapts the sampling schedule based on the observed internode data correlation as well as the temporal correlation. The performance of the algorithm has been assessed using real-world datasets. For two-tier networks, the proposed algorithm outperforms a highly cited previously published algorithm by up to 512% in terms of lifetime and by up to 30% in terms of prediction accuracy. For multihop networks, the proposed algorithm improves on the previously published algorithm by up to 553% and 38% in terms of lifetime and accuracy, respectively.