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Scientific and Statistical Database Management, International Conference on (2007)
Banff, Alberta, Canada
July 9, 2007 to July 11, 2007
ISSN: 1551-6393
ISBN: 0-7695-2868-6
pp: 26
Song Lin , University of California Riverside, USA
Benjamin Arai , University of California Riverside, USA
Dimitrios Gunopulos , University of California Riverside, USA
The ability to provide reliable in-network storage while balancing the energy consumption of individual sensors is a primary concern when deploying a sensor network. The main concern with data-centric storage in sensor networks is the ability to provide reliable and load balanced stor- age. Energy and wireless range constraints make central- ized approaches for storage impractical, and in-network data-centric solutions can be used to reduce the number of messages sent over the network. However, these solu- tions quickly become expensive when combined with fault- tolerance, load balancing and routing. In this paper, we present a novel data-centric storage and query routing mechanism for sensor networks. The routing mechanism is constructed upon the neighborhood information of indi- vidual sensors and is completely independent of geograph- ical information. Our data resilient algorithm is capable of recovering from multiple simultaneous failures in the net- work while adaptively adjusting the load distribution of the newly generated sensor data. Comprehensive experiments on both real-world and synthetic data sets indicate that our approach is more effective and efficient than the previously proposed solutions.

S. Lin, B. Arai and D. Gunopulos, "Reliable Hierarchical Data Storage in Sensor Networks," 2007 International Conference on Scientific and Statistical Database Management(SSDBM), Banff, Alta., 2007, pp. 26.
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