Efficient successor retrieval operations for aggregate query processing on clustered road networks

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buir.contributor.authorAykanat, Cevdet
dc.citation.epage2762en_US
dc.citation.issueNumber14en_US
dc.citation.spage2743en_US
dc.citation.volumeNumber180en_US
dc.contributor.authorDemir, E.en_US
dc.contributor.authorAykanat, Cevdeten_US
dc.date.accessioned2016-02-08T09:57:45Z
dc.date.available2016-02-08T09:57:45Z
dc.date.issued2010en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractGet-Successors (GS) which retrieves all successors of a junction is a kernel operation used to facilitate aggregate computations in road network queries. Efficient implementation of the GS operation is crucial since the disk access cost of this operation constitutes a considerable portion of the total query processing cost. Firstly, we propose a new successor retrieval operation Get-Unevaluated-Successors (GUS), which retrieves only the unevaluated successors of a given junction. The GUS operation is an efficient implementation of the GS operation, where the candidate successors to be retrieved are pruned according to the properties and state of the algorithm. Secondly, we propose a hypergraph-based model for clustering successively retrieved junctions by the GUS operations to the same pages. The proposed model utilizes query logs to correctly capture the disk access cost of GUS operations. The proposed GUS operation and associated clustering model are evaluated for two different instances of GUS operations which typically arise in Dijkstra's single source shortest path algorithm and incremental network expansion framework. Our simulation results show that the proposed successor retrieval operation together with the proposed clustering hypergraph model is quite effective in reducing the number of disk accesses in query processing. © 2010 Published by Elsevier Inc.en_US
dc.identifier.doi10.1016/j.ins.2010.03.015en_US
dc.identifier.issn0020-0255
dc.identifier.urihttp://hdl.handle.net/11693/22266
dc.language.isoEnglishen_US
dc.publisherElsevier Inc.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.ins.2010.03.015en_US
dc.source.titleInformation Sciencesen_US
dc.subjectClusteringen_US
dc.subjectData retrieval operationen_US
dc.subjectHypergraphsen_US
dc.subjectRoad networksen_US
dc.subjectStorage managementen_US
dc.titleEfficient successor retrieval operations for aggregate query processing on clustered road networksen_US
dc.typeArticleen_US

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