Rethinking Data Management for Storage-centric Sensor Networks

Data management in wireless sensor networks has been an area of significant research in recent years. Many existing sensor data management systems view sensor data as a continuous stream that is sensed, filtered, processed, and aggregated as it “flows” from sensors to users. We argue that technology trends in flash memories and embedded platforms call for re-thinking this architecture. We articulate a vision of a storage-centric sensor network where sensor nodes will be equipped with high-capacity and energy-efficient local flash storage. We argue that the data management infrastructure will need substantial redesign to fully exploit the presence of local storage and processing capability in order to reduce expensive communication. We then describe how StonesDB enables this vision through a number of innovative features including energyefficient use of flash memory, multi-resolution storage and aging, query processing, and intelligent caching.

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