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MANAGING MULTIDIMENSIONAL HISTORICAL AGGREGATE DATA IN UNSTRUCTURED P2P NETWORKS – SEPTEMBER 2010

Platform : DATA ENGINEERING / DATA MINING java

IEEE Projects Years : 2010

A P2P-based framework supporting the extraction of aggregates from historical multidimensional data is proposed, which provides efficient and robust query evaluation. When a data population is published, data are summarized in a synopsis, consisting of an index built on top of a set of subsynopses (storing compressed representations of distinct data portions). The index and the subsynopses are distributed across the network, and suitable replication mechanisms taking into account the query workload and network conditions are employed that provide the appropriate coverage for both the index and the subsynopses.

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