High-Performance Data Management and Efficient Aggregate Query Answering on Environmental Sensor Networks by Computational Grids

Data representation and query models are important limitations in managing sensor network data, since streams produced by sensors are theoretically unbounded. A possible solution consists in adopting the so-called data compression paradigm, which aims at computing compressed representations of summarized repositories collected from sensors, and then using these representations to efficiently answer aggregate queries. In this paper, we present a Grid framework based on the data compression paradigm, which allows us to provide facilities in both managing and querying sensor network data. We also present our experience in the context of a real-life system focused on the management of environmental sensor network data.