Managing Multidimensional Historical Aggregate Data in Unstructured P2P Networks

  • Authors:
  • Filippo Furfaro;Giuseppe M. Mazzeo;Andrea Pugliese

  • Affiliations:
  • University of Calabria, Rende;Institute of High Performance Computing and Networking of CNR National Council of Research (ICAR-CNR), Rende;University of Calabria, Rende

  • Venue:
  • IEEE Transactions on Knowledge and Data Engineering
  • Year:
  • 2010

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Abstract

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.