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dc.contributor.authorYilmaz, Okanen_US
dc.date.accessioned2014-03-14T20:19:11Z
dc.date.available2014-03-14T20:19:11Z
dc.date.issued2008-11-17en_US
dc.identifier.otheretd-11242008-103443en_US
dc.identifier.urihttp://hdl.handle.net/10919/29732
dc.description.abstractWe develop and analyze a class of CAC algorithms for resource management in wireless networks with the goal not only to satisfy QoS constraints, but also to maximize a value or reward objective function specified by the system. We demonstrate through analytical modeling and simulation validation that the CAC algorithms developed in this research for resource management can greatly improve the system reward obtainable with QoS guarantees, when compared with existing CAC algorithms designed for QoS satisfaction only. We design hybrid partitioning-threshold, spillover and elastic CAC algorithms based on the design techniques of partitioning, setting thresholds and probabilistic call acceptance to use channel resources for servicing distinct QoS classes. For each CAC algorithm developed, we identify optimal resource management policies in terms of partitioning or threshold settings to use channel resources. By comparing these CAC algorithms head-to-head under identical conditions, we determine the best algorithm to be used at runtime to maximize system reward with QoS guarantees for servicing multiple service classes in wireless networks. We study solution correctness, solution optimality and solution efficiency of the class of CAC algorithms developed. We ensure solution optimality by comparing optimal solutions achieved with those obtained by ideal CAC algorithms via exhaustive search. We study solution efficiency properties by performing complexity analyses and ensure solution correctness by simulation validation based on real human mobility data. Further, we analyze the tradeoff between solution optimality vs. solution efficiency and suggest the best CAC algorithm used to best tradeoff solution optimality for solution efficiency, or vice versa, to satisfy the systemâ s solution requirements. Moreover, we develop design principles that remain applicable despite rapidly evolving wireless network technologies since they can be generalized to deal with management of â resourcesâ (e.g., wireless channel bandwidth), â cellsâ (e.g., cellular networks), â connectionsâ (e.g., service calls with QoS constraints), and â reward optimizationâ (e.g., revenue optimization in optimal pricing determination) for future wireless service networks. To apply the CAC algorithms developed, we propose an application framework consisting of three stages: workload characterization, call admission control, and application deployment. We demonstrate the applicability with the optimal pricing determination application and the intelligent switch routing application.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartOkan-dissertation.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectresource management.en_US
dc.subjectwireless networksen_US
dc.subjectoptimal pricingen_US
dc.subjectreward optimizationen_US
dc.subjectperformance analysisen_US
dc.subjectCall admission controlen_US
dc.subjectquality of serviceen_US
dc.titleA Class of Call Admission Control Algorithms for Resource Management and Reward Optimization for Servicing Multiple QoS Classes in Wireless Networks and Its Applicationsen_US
dc.typeDissertationen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Scienceen_US
dc.contributor.committeechairChen, Ing-Rayen_US
dc.contributor.committeememberFrakes, William B.en_US
dc.contributor.committeememberKulczycki, Gregory W.en_US
dc.contributor.committeememberEltoweissy, Mohamed Y.en_US
dc.contributor.committeememberEgyhazy, Csaba J.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11242008-103443/en_US
dc.date.sdate2008-11-24en_US
dc.date.rdate2008-12-17
dc.date.adate2008-12-17en_US


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