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Scalable traffic-aware virtual machine management for cloud data centers
conference contribution
posted on 2018-07-31, 15:23 authored by Fung Po TsoFung Po Tso, Konstantinos Oikonomou, Eleni Kavvadia, Dimitrios P. PezarosVirtual Machine (VM) management is a powerful mechanism for providing elastic services over Cloud Data Centers (DC)s. At the same time, the resulting network congestion has been repeatedly reported as the main bottleneck in DCs, even when the overall resource utilization of the infrastructure remains low. However, most current VM management strategies are traffic-agnostic, while the few that are traffic-aware only concern a static initial allocation, ignore bandwidth oversubscription, or do not scale. In this paper we present S-CORE, a scalable VM migration algorithm to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We formulate the aggregate VM communication as an optimization problem and we then define a novel distributed migration scheme that iteratively adapts to dynamic traffic changes. Through extensive simulation and implementation results, we show that S-CORE achieves significant (up to 87%) communication cost reduction while incurring minimal overhead and downtime.
History
School
- Science
Department
- Computer Science
Published in
IEEE 34th International Conference on Distributed Computing Systems (ICDCS)Citation
TSO, F.P. ... et al, 2014. Scalable traffic-aware virtual machine management for cloud data centers. IN: IEEE 34th International Conference on Distributed Computing Systems (ICDCS), Madrid, Spain, 30 June-3 July 2014, pp.238-247.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publication date
2014-09-01Notes
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISSN
1063-6927Publisher version
Language
- en