Parallel and Distributed Databases: Introduction

Djoerd Hiemstra, Alfons Kemper, Manuel Prieto, Alex Szalay

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Euro-Par Topic 5 addresses data management issues in parallel and distributed computing. Advances in data management (storage, access, querying, retrieval, mining) are inherent to current and future information systems. Today, accessing large volumes of information is a reality: Data-intensive applications enable huge user communities to transparently access multiple pre-existing autonomous, distributed and heterogeneous resources (data, documents, images, services, etc.). Data management solutions need efficient techniques for exploiting and mining large datasets available in clusters, peer to peer and Grid architectures. Parallel and distributed file systems, databases, data warehouses, and digital libraries are a key element for achieving scalable, efficient systems that will cost-effectively manage and extract data from huge amounts of highly distributed and heterogeneous digital data repositories. Each paper submitted to Euro-Par’s topic Parallel and Distributed Databases was reviewed by at least three reviewers. Of 11 papers submitted to the topic this year, 3 were accepted, which makes an acceptance rate of 27 %. The three accepted papers discuss diverse issues: database transactions, efficient and reliable structured peer-to-peer systems, and selective replicated declustering.
Original languageUndefined
Title of host publicationEuro-Par 2009 Parallel Processing
Place of PublicationBerlin
Number of pages2
ISBN (Print)978-3-642-03868-6
Publication statusPublished - Aug 2009
Event14th International Euro-Par Conference on Parallel Processing, Euro-Par 2009 - Delft, Netherlands
Duration: 25 Aug 200928 Aug 2009
Conference number: 14

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Euro-Par Conference on Parallel Processing, Euro-Par 2009
Abbreviated titleEuro-Par


  • METIS-264286
  • EWI-17093
  • IR-69238

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