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Article: Processing continuous range queries with spatiotemporal tolerance

TitleProcessing continuous range queries with spatiotemporal tolerance
Authors
Keywordscontinuous queries
data uncertainty
distributed processing
energy consumption.
Tracking mobile objects
Issue Date2011
PublisherIEEE.
Citation
Ieee Transactions On Mobile Computing, 2011, v. 10 n. 3, p. 320-334 How to Cite?
AbstractContinuous queries are often employed to monitor the locations of mobile objects (MOs), which are determined by sensing devices like GPS receivers. In this paper, we tackle two challenges in processing continuous range queries (CRQs): coping with data uncertainty inherently associated with location data, and reducing the energy consumption of battery-powered MOs. We propose the concept of spatiotemporal tolerance for CRQ to relax a query's accuracy requirements in terms of a maximal acceptable error. Unlike previous works, our definition considers tolerance in both the spatial and temporal dimensions, which offers applications more flexibility in specifying their individual accuracy requirements. As we will show, these tolerance bounds can provide well-defined query semantics in spite of different sources of data uncertainty. In addition, we present efficient algorithms that carefully control when an MO should sense or report a location, while satisfying these tolerances. Thereby, we particularly reduce the number of position sensing operations substantially, which constitute a considerable source of energy consumption. Extensive simulations confirm that the proposed algorithms result in large energy savings compared to nontolerant query processing. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/127358
ISSN
2015 Impact Factor: 2.456
2015 SCImago Journal Rankings: 1.826
ISI Accession Number ID
Funding AgencyGrant Number
German Research Foundation (DFG) within the Collaborative Research Center(SFB) 627
Germany/Hong Kong Joint Research Scheme (DAAD)PPP D/06/00383
G_HK013/06
Research Grants Council of Hong KongHKU 513307E
HKU 513508E
HKU 711309E
University of Hong Kong200808159002
Funding Information:

The joint work described in this paper was supported by the German Research Foundation (DFG) within the Collaborative Research Center (SFB) 627, by the Germany/Hong Kong Joint Research Scheme (DAAD PPP D/06/00383, G_HK013/06), by the Research Grants Council of Hong Kong (Projects HKU 513307E, HKU 513508E, and HKU 711309E), and by the Seed Funding Programme of the University of Hong Kong (grant no. 200808159002). The authors also thank the reviewers for their insightful comments.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorFarrell, Ten_HK
dc.contributor.authorRothermel, Ken_HK
dc.contributor.authorCheng, Ren_HK
dc.date.accessioned2010-10-31T13:20:56Z-
dc.date.available2010-10-31T13:20:56Z-
dc.date.issued2011en_HK
dc.identifier.citationIeee Transactions On Mobile Computing, 2011, v. 10 n. 3, p. 320-334en_HK
dc.identifier.issn1536-1233en_HK
dc.identifier.urihttp://hdl.handle.net/10722/127358-
dc.description.abstractContinuous queries are often employed to monitor the locations of mobile objects (MOs), which are determined by sensing devices like GPS receivers. In this paper, we tackle two challenges in processing continuous range queries (CRQs): coping with data uncertainty inherently associated with location data, and reducing the energy consumption of battery-powered MOs. We propose the concept of spatiotemporal tolerance for CRQ to relax a query's accuracy requirements in terms of a maximal acceptable error. Unlike previous works, our definition considers tolerance in both the spatial and temporal dimensions, which offers applications more flexibility in specifying their individual accuracy requirements. As we will show, these tolerance bounds can provide well-defined query semantics in spite of different sources of data uncertainty. In addition, we present efficient algorithms that carefully control when an MO should sense or report a location, while satisfying these tolerances. Thereby, we particularly reduce the number of position sensing operations substantially, which constitute a considerable source of energy consumption. Extensive simulations confirm that the proposed algorithms result in large energy savings compared to nontolerant query processing. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.-
dc.relation.ispartofIEEE Transactions on Mobile Computingen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsIEEE Transactions on Mobile Computing. Copyright © IEEE.-
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectcontinuous queriesen_HK
dc.subjectdata uncertaintyen_HK
dc.subjectdistributed processingen_HK
dc.subjectenergy consumption.en_HK
dc.subjectTracking mobile objectsen_HK
dc.titleProcessing continuous range queries with spatiotemporal toleranceen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1536-1233&volume=10&issue=3&spage=320&epage=334&date=2011&atitle=Processing+continuous+range+queries+with+spatiotemporal+tolerance-
dc.identifier.emailCheng, R:ckcheng@cs.hku.hken_HK
dc.identifier.authorityCheng, R=rp00074en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TMC.2010.159en_HK
dc.identifier.scopuseid_2-s2.0-78751626011en_HK
dc.identifier.hkuros175901en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78751626011&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume10en_HK
dc.identifier.issue3en_HK
dc.identifier.spage320en_HK
dc.identifier.epage334en_HK
dc.identifier.isiWOS:000286205600002-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectAdaptive Filters for Continuous Queries over Constantly-Evolving Data Streams-
dc.relation.projectEfficient Protocols for Quality-Aware Querying of Sensor Data in Pervasive Environments-
dc.relation.projectScalable Cleaning of Probabilistic Databases with Quality Guarantees-
dc.relation.projectScalable Continuous Query Processing on Imprecise Location Data-
dc.identifier.scopusauthoridFarrell, T=24724041900en_HK
dc.identifier.scopusauthoridRothermel, K=24484086200en_HK
dc.identifier.scopusauthoridCheng, R=7201955416en_HK
dc.identifier.citeulike7730985-

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