Authors: Song Lin, Benjamin Arai, Dimitrios Gunopulos
Title: Reliable Hierarchical Data Storage in Sensor Networks
Conference: Statistical and Scientific Database Management (SSDBM)
Abstract: When deploying a sensor network, a major concern is the ability to provide reliable in-network storage while balancing the energy consumption of individual sensors. The main concern with data-centric storage in sensor networks is the ability to provide reliable, load-balanced storage. Energy and wireless range constraints make centralized 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 solutions quickly become expensive when combined with faulttolerance, load balancing and routing. In this paper, we present novel, data-centric storage and query routing mechanisms for sensor networks. The query routing mechanism is constructed with the neighborhood information of individual sensors and is completely independent of geographical information. Our data-resilient algorithm is capable of recovering from multiple simultaneous failures in the network while adaptively adjusting the load distribution of 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.