Abstract
This paper presents our experience in experimenting the query performance of a Grid-based sensor network data warehouse, which encompasses several metaphors of data compression/approximation and high performance and high reliability computing that are typical of Grid architectures. Our experimentation focuses on two main classes of aggregate range queries over sensor readings, namely (i) the window queries, which apply a SQL aggregation operator over a fixed window over the reading stream produced by the sensor network, and (ii) the continuous queries, which instead consider a “moving” window, and produce as output a stream of answers. Both classes of queries are extremely useful to extract summarized knowledge to be exploited by OLAP-like analysis tools over sensor network data. The experimental results, conducted on several synthetic data sets, clearly confirm the benefits deriving from embedding the data compression/approximation paradigm into Grid-based sensor network data warehouses.
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Cuzzocrea, A., Kumar, A., Russo, V. (2008). Experimenting the Query Performance of a Grid-Based Sensor Network Data Warehouse. In: Hameurlain, A. (eds) Data Management in Grid and Peer-to-Peer Systems. Globe 2008. Lecture Notes in Computer Science, vol 5187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85176-9_10
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DOI: https://doi.org/10.1007/978-3-540-85176-9_10
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