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Article: Processing continuous range queries with spatiotemporal tolerance
Title | Processing continuous range queries with spatiotemporal tolerance | ||||||||||
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Authors | |||||||||||
Keywords | continuous queries data uncertainty distributed processing energy consumption. Tracking mobile objects | ||||||||||
Issue Date | 2011 | ||||||||||
Publisher | IEEE. | ||||||||||
Citation | Ieee Transactions On Mobile Computing, 2011, v. 10 n. 3, p. 320-334 How to Cite? | ||||||||||
Abstract | Continuous 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 Identifier | http://hdl.handle.net/10722/127358 | ||||||||||
ISSN | 2023 Impact Factor: 7.7 2023 SCImago Journal Rankings: 2.755 | ||||||||||
ISI Accession Number ID |
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 Field | Value | Language |
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dc.contributor.author | Farrell, T | en_HK |
dc.contributor.author | Rothermel, K | en_HK |
dc.contributor.author | Cheng, R | en_HK |
dc.date.accessioned | 2010-10-31T13:20:56Z | - |
dc.date.available | 2010-10-31T13:20:56Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | Ieee Transactions On Mobile Computing, 2011, v. 10 n. 3, p. 320-334 | en_HK |
dc.identifier.issn | 1536-1233 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/127358 | - |
dc.description.abstract | Continuous 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.language | eng | en_HK |
dc.publisher | IEEE. | - |
dc.relation.ispartof | IEEE Transactions on Mobile Computing | en_HK |
dc.rights | ©2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | continuous queries | en_HK |
dc.subject | data uncertainty | en_HK |
dc.subject | distributed processing | en_HK |
dc.subject | energy consumption. | en_HK |
dc.subject | Tracking mobile objects | en_HK |
dc.title | Processing continuous range queries with spatiotemporal tolerance | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://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.email | Cheng, R:ckcheng@cs.hku.hk | en_HK |
dc.identifier.authority | Cheng, R=rp00074 | en_HK |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/TMC.2010.159 | en_HK |
dc.identifier.scopus | eid_2-s2.0-78751626011 | en_HK |
dc.identifier.hkuros | 175901 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-78751626011&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 10 | en_HK |
dc.identifier.issue | 3 | en_HK |
dc.identifier.spage | 320 | en_HK |
dc.identifier.epage | 334 | en_HK |
dc.identifier.isi | WOS:000286205600002 | - |
dc.publisher.place | United States | en_HK |
dc.relation.project | Adaptive Filters for Continuous Queries over Constantly-Evolving Data Streams | - |
dc.relation.project | Efficient Protocols for Quality-Aware Querying of Sensor Data in Pervasive Environments | - |
dc.relation.project | Scalable Cleaning of Probabilistic Databases with Quality Guarantees | - |
dc.relation.project | Scalable Continuous Query Processing on Imprecise Location Data | - |
dc.identifier.scopusauthorid | Farrell, T=24724041900 | en_HK |
dc.identifier.scopusauthorid | Rothermel, K=24484086200 | en_HK |
dc.identifier.scopusauthorid | Cheng, R=7201955416 | en_HK |
dc.identifier.citeulike | 7730985 | - |
dc.identifier.issnl | 1536-1233 | - |