Aggregate queries are useful in the context of sensor networkbased systems as they retrieve knowledge from huge amounts of summarized readings to be exploited for knowledge discovery purposes. Actually, data representation and query models are important limitations in managing sensor network data, since streams produced by sensors are theoretically unbounded. In this paper, we present a Grid framework, based on the data compression paradigm, which allows us to provide approximate answers to aggregate queries on summarized 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.
A Grid Framework for High-Performance Data Management and Efficient Aggregate Query Answering on Environmental Sensor Networks .
2008
Abstract
Aggregate queries are useful in the context of sensor networkbased systems as they retrieve knowledge from huge amounts of summarized readings to be exploited for knowledge discovery purposes. Actually, data representation and query models are important limitations in managing sensor network data, since streams produced by sensors are theoretically unbounded. In this paper, we present a Grid framework, based on the data compression paradigm, which allows us to provide approximate answers to aggregate queries on summarized 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
