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Index-based query processing on distributed multidimensional data

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dc.contributor.author Tsatsanifos, G en
dc.contributor.author Sacharidis, D en
dc.contributor.author Sellis, T en
dc.date.accessioned 2014-03-01T11:47:00Z
dc.date.available 2014-03-01T11:47:00Z
dc.date.issued 2012 en
dc.identifier.issn 13846175 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/38058
dc.subject Distributed index en
dc.subject Distributed query processing en
dc.subject Nearest neighbor query en
dc.subject Peer-to-peer networks en
dc.title Index-based query processing on distributed multidimensional data en
heal.type other en
heal.identifier.primary 10.1007/s10707-012-0163-x en
heal.identifier.secondary http://dx.doi.org/10.1007/s10707-012-0163-x en
heal.publicationDate 2012 en
heal.abstract This work introduces decentralized query processing techniques based on MIDAS, a novel distributed multidimensional index. In particular, MIDAS implements a distributed k-d tree, where leaves correspond to peers, and internal nodes dictate message routing. MIDAS requires that peers maintain little network information, and features mechanisms that support fault tolerance and load balancing. The proposed algorithms process point and range queries over the multidimensional indexed space in only O(log n) hops in expectance, where n is the network size. For nearest neighbor queries, two processing alternatives are discussed. The first, termed eager processing, has low latency (expected value of O(log n) hops) but may involve a large number of peers. The second, termed iterative processing, has higher latency (expected value of O(log2n) hops) but involves far fewer peers. A detailed experimental evaluation demonstrates that our query processing techniques outperform existing methods for settings involving real spatial data as well as in the case of high dimensional synthetic data. © 2012 Springer Science+Business Media, LLC. en
heal.journalName GeoInformatica en
dc.identifier.doi 10.1007/s10707-012-0163-x en
dc.identifier.spage 1 en
dc.identifier.epage 31 en


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