Mobiiscape: Middleware support for scalable mobility pattern monitoring of moving objects in a large-scale city

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dc.contributor.authorKim, Byoungjipko
dc.contributor.authorLee, SangJeongko
dc.contributor.authorLee, Youngkiko
dc.contributor.authorHwang, Inseokko
dc.contributor.authorRhee, Yunseokko
dc.contributor.authorSong, Junehwako
dc.date.accessioned2013-03-09T02:18:59Z-
dc.date.available2013-03-09T02:18:59Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2011-11-
dc.identifier.citationJOURNAL OF SYSTEMS AND SOFTWARE, v.84, no.11, pp.1852 - 1870-
dc.identifier.issn0164-1212-
dc.identifier.urihttp://hdl.handle.net/10203/95104-
dc.description.abstractWith the explosive proliferation of mobile devices such as smartphones, tablets, and sensor nodes, location-based services are getting even more attention than before, considered as one of the killer applications in the upcoming mobile computing era. Developing location-based services necessarily requires an effective and scalable location data processing technology. In this paper, we present Mobiiscape, a novel location monitoring system that collectively monitors mobility patterns of a large number of moving objects in a large-scale city to support city-wide mobility-aware applications. Mobiiscape provides an SQL-like query language named Moving Object Monitoring Query Language (MQL) that allows applications to intuitively specify Mobility Pattern Monitoring Queries (MPQs). Further, Mobiiscape provides a set of scalable location monitoring techniques to efficiently process a large number of MPQs over a large number of location streams. The scalable processing techniques include a (1) Place Border Index, a spatial index for quickly searching for relevant queries upon receiving location streams, (2) Place-Based Window, a spatial-purpose window for efficiently detecting primitive mobility patterns, (3)Shared NFA, a shared query processing technique for efficiently matching complex mobility patterns, and (4) Attribute Pre-matching Bitmap, an in-memory data structure for efficiently filtering out moving objects based on their attributes. We have implemented a Mobiiscape prototype system. Then, we show the usefulness of the system by implementing promising location-based applications based on it such as a ubiquitous taxicab service and a location-based advertising. Also, we demonstrate the performance benefit of the system through extensive evaluation and comparison. (C) 2011 Elsevier Inc. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE INC-
dc.titleMobiiscape: Middleware support for scalable mobility pattern monitoring of moving objects in a large-scale city-
dc.typeArticle-
dc.identifier.wosid000295997900003-
dc.identifier.scopusid2-s2.0-80052771296-
dc.type.rimsART-
dc.citation.volume84-
dc.citation.issue11-
dc.citation.beginningpage1852-
dc.citation.endingpage1870-
dc.citation.publicationnameJOURNAL OF SYSTEMS AND SOFTWARE-
dc.contributor.localauthorSong, Junehwa-
dc.contributor.nonIdAuthorRhee, Yunseok-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorLocation-based services-
dc.subject.keywordAuthorMobility pattern monitoring-
dc.subject.keywordAuthorLocation stream processing-
dc.subject.keywordAuthorComplex event processing-
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