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dc.contributor.authorTsygankov, Mykolaen_US
dc.contributor.authorChen, Chienen_US
dc.date.accessioned2018-08-21T05:57:07Z-
dc.date.available2018-08-21T05:57:07Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn1944-0375en_US
dc.identifier.urihttp://hdl.handle.net/11536/147068-
dc.description.abstractDespite being industry standard, load balancing via virtual machine (VM) migration methods in modern cloud data centers still exhibit two major performance issues: resulting system load balancing degree and total time till balanced state. Over the years research has been conducted to improve these metrics. Yet due to the fact that these issues influence each other, it has been a challenge to achieve substantial advancement in both metrics simultaneously. In this paper we study the problem of VM migration with load balancing and migration time constraints. We formulate this problem as a variation of multi-commodity minimum cost flow problem and show how both resulting degree of imbalance and a total migration time can be optimized together. We also propose a heuristic method based on Ant Colony Optimization family of algorithms. Through simulation results we show that our heuristic gives good performance results compared to optimal solutions to minimum cost flow problem. Furthermore, our method achieves on average twice faster migration time compared to existing methods, proposed in related works.en_US
dc.language.isoen_USen_US
dc.subjectClouden_US
dc.subjectData Centeren_US
dc.subjectLoad Balancingen_US
dc.subjectVM Migrationen_US
dc.subjectMigration Timeen_US
dc.subjectMulti-Commodity Flowen_US
dc.subjectSDNen_US
dc.subjectAnt Colony Systemen_US
dc.titleNetwork Aware VM Load Balancing in Cloud Data Centers Using SDNen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 23RD IEEE INTERNATIONAL SYMPOSIUM ON LOCAL AND METROPOLITAN AREA NETWORKS (LANMAN)en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000426966200051en_US
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