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Data Reduction Algorithm on the Monitoring of Extreme Values in WSNs
Authors:
Chun-Lung Lin
Pei-Hsuan Tsai
Hsiao-Chuan Liang
Jia-Shung Wang
Keywords: sensor networks; extreme values; data reduction.
Abstract:
Monitoring extreme values (maximum or minimum) is important to many applications in wireless sensor networks. A previous work, called Hierarchy Adaptive Threshold (HAT), proposed a tree-based structure to distribute queries efficiently and filter out the unnecessary data updates that are not extreme values. In this paper, a data reduction algorithm is presented to reduce energy consumption of the HAT due to network transmission. The proposed method utilizes historical information of extreme values and their corresponding node ID to adjust the reporting rate of sensors properly and eases the burden of the parent of extreme nodes by balancing the packets from extreme nodes to all their possible parents. We evaluate the performance of the proposed algorithm by NS-2 network simulator and real-world data traces. The results indicate that the overall network packets are reduced to 80% with 1% data error in comparison with HAT.
Pages: 6 to 13
Copyright: Copyright (c) IARIA, 2012
Publication date: August 19, 2012
Published in: conference
ISSN: 2308-4405
ISBN: 978-1-61208-207-3
Location: Rome, Italy
Dates: from August 19, 2012 to August 24, 2012