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Efficient gathering of correlated data in sensor networks

Content Provider	ACM Digital Library
Author	Chowdhary, Vishal Gupta, Himanshu Das, Samir Navda, Vishnu
Copyright Year	2008
Abstract	In this article, we design techniques that exploit data correlations in sensor data to minimize communication costs (and hence, energy costs) incurred during data gathering in a sensor network. Our proposed approach is to select a small subset of sensor nodes that may be sufficient to reconstruct data for the entire sensor network. Then, during data gathering only the selected sensors need to be involved in communication. The selected set of sensors must also be connected, since they need to relay data to the data-gathering node. We define the problem of selecting such a set of sensors as the connected correlation-dominating set problem, and formulate it in terms of an appropriately defined correlation structure that captures general data correlations in a sensor network. We develop a set of energy-efficient distributed algorithms and competitive centralized heuristics to select a connected correlation-dominating set of small size. The designed distributed algorithms can be implemented in an asynchronous communication model, and can tolerate message losses. We also design an exponential (but nonexhaustive) centralized approximation algorithm that returns a solution within $\textit{O}(log$ $\textit{n})$ of the optimal size. Based on the approximation algorithm, we design a class of centralized heuristics that are empirically shown to return near-optimal solutions. Simulation results over randomly generated sensor networks with both artificially and naturally generated data sets demonstrate the efficiency of the designed algorithms and the viability of our technique—even in dynamic conditions.
Starting Page	1
Ending Page	31
Page Count	31
File Format	PDF
ISSN	15504859
e-ISSN	15504867
DOI	10.1145/1325651.1325655
Volume Number	4
Issue Number	1
Journal	ACM Transactions on Sensor Networks (TOSN)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-02-11
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Correlated Data Energy Efficiency Topology Control
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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