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dc.contributor.authorBairley, Alan
dc.contributor.authorXie, Geoffrey
dc.contributor.authorCarlyle, Matthew
dc.date.accessioned2016-06-27T14:39:32Z
dc.date.available2016-06-27T14:39:32Z
dc.date.issued2016-06-09
dc.identifier.urihttp://hdl.handle.net/10945/48963
dc.descriptionApproved for public release; distribution is unlimited.
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 objectives, is a challenging open problem.In this work, we formulate SDN orchestration as a multiobjective optimization problem, and present an evolutionary approach designed to explore the NCF tradeoff space comprehensively and avoid local optima.For an instance of the VM allocation problem subject to three independent NCFs optimizing network survivability, bandwidth efficiency, and power consumption, respectively, we demonstrate that our approach can enumerate a wider range of, and potentially better solutions than current orchestrators, for data centers with 100s of switches, 1,000s of servers, and 10,000s of VM slots.en_US
dc.description.sponsorshipOffice of the Department of Defense, Chief Information Officer, 6000 Defense Pentagon, Washington, D.C. 20301-6000en_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.titleTowards optimal orchestration of network control functions: an evolutionary approachen_US
dc.typeTechnical Report
dc.contributor.departmentComputer Scienceen_US
dc.subject.authorSoftware-Defined Networkingen_US
dc.subject.authorNetwork Stateen_US
dc.subject.authorDatacenter Networken_US
dc.subject.authorGenetic Algorithmsen_US
dc.description.funderDepartment of Defense Information Assurance Scholarship Program (DoD IASP).en_US
dc.identifier.npsreportNPS-CS-16-002en_US


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