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dc.contributor.advisorXie, Geoffrey G.
dc.contributor.authorBairley, Alan M.
dc.dateDec-16
dc.date.accessioned2017-02-09T00:02:40Z
dc.date.available2017-02-09T00:02:40Z
dc.date.issued2016-12
dc.identifier.urihttp://hdl.handle.net/10945/51606
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractSoftware-defined network (SDN) orchestration, the problem of integrating and deploying multiple network control functions (NCFs) while minimizing suboptimal network states that can result from competing NCF proposals, is a challenging open problem. In this work, we formulate SDN orchestration as a multiobjective optimization problem, present an evolutionary algorithm designed to explore the NCF tradeoff space comprehensively and avoid local optima, and propose a new application-aware approach that explicitly models resource preferences of individual application workloads. Further, we propose a new logical application workload (LAW) abstraction to enable precomputation of the required relative positioning of an application's virtual machines (VMs) and allocation of these VMs in a single atomic step, leading to online algorithms that are one order of magnitude faster than existing solutions for placing data center workloads. For an instance of the SDN orchestration problem subject to four independent NCFs attempting to optimize network survivability, bandwidth efficiency, power conservation, and computational contention, we demonstrate that our approach enumerates a wider range of, and potentially better, solutions than current orchestrators, for data centers with hundreds of switches, thousands of servers, and tens of thousands of VM slots.en_US
dc.description.urihttp://archive.org/details/efficientorchest1094551606
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleEfficient orchestration of data centers via comprehensive and application-aware trade-off explorationen_US
dc.typeThesisen_US
dc.contributor.departmentComputer Science (CS)
dc.subject.authorsoftware-defined networkingen_US
dc.subject.authornetwork stateen_US
dc.subject.authordata center networken_US
dc.subject.authorgenetic algorithmsen_US
dc.subject.authorvirtual machine placementen_US
dc.description.serviceMajor, United States Armyen_US
etd.thesisdegree.nameDoctor of Philosophy in Computer Scienceen_US
etd.thesisdegree.levelDoctoralen_US
etd.thesisdegree.disciplineComputer Scienceen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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