Issue No. 09 - September (2010 vol. 22)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2009.160
Filippo Furfaro , University of Calabria, Rende
Giuseppe Massimiliano Mazzeo , Institute of High Performance Computing and Networking of CNR National Council of Research (ICAR-CNR), Rende
Andrea Pugliese , University of Calabria, Rende
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.
P2P networks, multidimensional data management, data compression.
G. M. Mazzeo, A. Pugliese and F. Furfaro, "Managing Multidimensional Historical Aggregate Data in Unstructured P2P Networks," in IEEE Transactions on Knowledge & Data Engineering, vol. 22, no. , pp. 1313-1330, 2009.