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dc.contributor.authorPesti, Peteren_US
dc.date.accessioned2013-01-17T21:46:37Z
dc.date.available2013-01-17T21:46:37Z
dc.date.issued2012-11-12en_US
dc.identifier.urihttp://hdl.handle.net/1853/45844
dc.description.abstractLocation based services (LBS) are gaining widespread user acceptance and increased daily usage. GPS based mobile navigation systems (Garmin), location-related social network updates and "check-ins" (Facebook), location-based games (Nokia), friend queries (Foursquare) and ads (Google) are some of the popular LBSs available to mobile users today. Despite these successes, current user services fall short of a vision where mobile users could ask for continuous location-based services with always-up-to-date information around them, such as the list of friends or favorite restaurants within 15 minutes of driving. Providing such a location based service in real time faces a number of technical challenges. In this dissertation research, we propose a suite of novel techniques and system architectures to address some known technical challenges of continuous location queries and updates. Our solution approaches enable the creation of new, practical and scalable location based services with better energy efficiency on mobile clients and higher throughput at the location servers. Our first contribution is the development of RoadTrack, a road network aware and query-aware location update framework and a suite of algorithms. A unique characteristic of RoadTrack is the innovative design of encounter points and system-defined precincts to manage the desired spatial resolution of location updates for different mobile clients while reducing the complexity and energy consumption of location update strategies. The second novelty of this dissertation research is the technical development of Dandelion data structures and algorithms that can deliver superior performance for the periodic re-evaluation of continuous road-network distance based location queries, when compared with the alternative of repeatedly performing a network expansion along a mobile user's trajectory. The third contribution of this dissertation research is the FastExpand algorithm that can speed up the computation of single-issue shortest-distance road network queries. Finally, we have developed the open source GT MobiSim mobility simulator, a discrete event simulation platform to generate realistic driving trajectories for real road maps. It has been downloaded and utilized by many to evaluate the efficiency and effectiveness of the location query and location update algorithms, including the research efforts in this dissertation.en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectCQen_US
dc.subjectRange queryen_US
dc.subjectRoad networken_US
dc.subjectSimulationen_US
dc.subjectLbsen_US
dc.subjectLocation based servicesen_US
dc.subjectMobileen_US
dc.subjectQueryen_US
dc.subjectContinuous queryen_US
dc.subject.lcshQuerying (Computer science)
dc.subject.lcshDatabase searching
dc.subject.lcshSystem design
dc.titleNovel spatial query processing techniques for scaling location based servicesen_US
dc.typeDissertationen_US
dc.description.degreePhDen_US
dc.contributor.departmentComputingen_US
dc.description.advisorCommittee Chair: Liu, Ling; Committee Member: Choi, Wonik; Committee Member: Mark, Leo; Committee Member: Omiecinski, Edward; Committee Member: Pu, Caltonen_US


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