Title:
Novel spatial query processing techniques for scaling location based services

dc.contributor.advisor Liu, Ling
dc.contributor.author Pesti, Peter en_US
dc.contributor.committeeMember Choi, Wonik
dc.contributor.committeeMember Mark, Leo
dc.contributor.committeeMember Omiecinski, Edward
dc.contributor.committeeMember Pu, Calton
dc.contributor.department Computing en_US
dc.date.accessioned 2013-01-17T21:46:37Z
dc.date.available 2013-01-17T21:46:37Z
dc.date.issued 2012-11-12 en_US
dc.description.abstract Location 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.description.degree PhD en_US
dc.identifier.uri http://hdl.handle.net/1853/45844
dc.publisher Georgia Institute of Technology en_US
dc.subject CQ en_US
dc.subject Range query en_US
dc.subject Road network en_US
dc.subject Simulation en_US
dc.subject Lbs en_US
dc.subject Location based services en_US
dc.subject Mobile en_US
dc.subject Query en_US
dc.subject Continuous query en_US
dc.subject.lcsh Querying (Computer science)
dc.subject.lcsh Database searching
dc.subject.lcsh System design
dc.title Novel spatial query processing techniques for scaling location based services en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Liu, Ling
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computer Science
relation.isAdvisorOfPublication 96391b98-ac42-4e2c-93ee-79a5e16c2dfb
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 6b42174a-e0e1-40e3-a581-47bed0470a1e
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