Latest revision as of 19:05, 28 January 2021

Abstract

Today's data centers need efficient traffic management to improve resource utilization in their networks. In this work, we study a joint tenant (e.g., server or virtual machine) placement and routing problem to minimize traffic costs. These two complementary degrees of freedom—placement and routing—are mutually-dependent, however, are often optimized separately in today's data centers. Leveraging and expanding the technique of Markov approximation, we propose an efficient online algorithm in a dynamic environment under changing traffic loads. The algorithm requires a very small number of virtual machine migrations and is easy to implement in practice. Performance evaluation that employs the real data center traffic traces under a spectrum of elephant and mice flows, demonstrates a consistent and significant improvement over the benchmark achieved by common heuristics.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.1109/infcom.2012.6195719

• http://www.seas.gwu.edu/~tlan/papers/vm_placement_routing.pdf

• http://xplorestaging.ieee.org/ielx5/6189419/6195452/06195719.pdf?arnumber=6195719,

http://dx.doi.org/10.1109/infcom.2012.6195719

• https://dblp.uni-trier.de/db/conf/infocom/infocom2012.html#JiangLHCC12,

https://ieeexplore.ieee.org/document/6195719,

http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000006195719,

http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6195719&abstractAccess=no&userType=inst,

https://doi.org/10.1109/INFCOM.2012.6195719,

https://xplqa30.ieee.org/document/6195719,

https://collaborate.princeton.edu/en/publications/joint-vm-placement-and-routing-for-data-center-traffic-engineerin,

https://academic.microsoft.com/#/detail/2039612281