A P2P-based framework supporting the extraction of aggregates from historical multi-dimensional 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 sub-synopses (storing compressed representations of distinct data portions). The index and the sub-synopses 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 sub-synopses.
Index Terms:
Distributed applications, Data compaction and compression
Citation:
Filippo Furfaro, Giuseppe M. Mazzeo, Andrea Pugliese, "Managing Multi-Dimensional Historical Aggregate Data in Unstructured P2P Systems," IEEE Transactions on Knowledge and Data Engineering, 02 Jul. 2009. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TKDE.2009.160>