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.
Citation:
Song Lin, Benjamin Arai, Dimitrios Gunopulos, "Reliable Hierarchical Data Storage in Sensor Networks," ssdbm, pp.26, 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007), 2007