SDN-Based Multi-Class QoS Guarantee in Inter-Data Center Communications

In this paper, we describe a software defined networking (SDN) approach to traffic engineering in inter-data center communication; then present <inline-formula><tex-math notation="LaTeX">$\mathrm{MCTEQ}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq1-2491930.gif"/></alternatives></inline-formula>, a constrained utility-optimization formulation of the joint-bandwidth allocation problem for multiple classes of traffic in inter-data center communication. <inline-formula><tex-math notation="LaTeX">$\mathrm{MCTEQ}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq2-2491930.gif"/></alternatives></inline-formula> handles priorities between traffic classes in a soft manner and explicitly considers the delay requirement of <inline-formula><tex-math notation="LaTeX">$\mathrm{Interactive}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq3-2491930.gif"/></alternatives></inline-formula> flows. <inline-formula><tex-math notation="LaTeX">$\mathrm{MCTEQ}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq4-2491930.gif"/></alternatives></inline-formula> being NP-hard, we construct a new approximation to be able to lean on the mature and efficient linear programming solvers to obtain fast and accurate approximations. We demonstrate via numerical experiments with two realistic inter-data center network topologies that <inline-formula><tex-math notation="LaTeX">$\mathrm{MCTEQ}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq5-2491930.gif"/></alternatives></inline-formula> achieves considerably more network utilization than the best known solutions from the literature, while running at least twice faster. We also show via ns-2 packet level simulation that with <inline-formula><tex-math notation="LaTeX">$\mathrm{MCTEQ}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq6-2491930.gif"/></alternatives></inline-formula> traffic engineering, end-to-end packet delay requirements of <inline-formula><tex-math notation="LaTeX">$\mathrm{Interactive}$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq7-2491930.gif"/></alternatives></inline-formula> flows are indeed guaranteed for in-profile traffic, which is not the case for alternative approaches.

[1]  R. Braatz,et al.  A tutorial on linear and bilinear matrix inequalities , 2000 .

[2]  Srikanth Kandula,et al.  Traffic engineering with forward fault correction , 2014, SIGCOMM.

[3]  J. Rexford,et al.  Scalable Multi-Class Traffic Management in Data Center Backbone Networks , 2013, IEEE Journal on Selected Areas in Communications.

[4]  S. Jamaloddin Golestani,et al.  A self-clocked fair queueing scheme for broadband applications , 1994, Proceedings of INFOCOM '94 Conference on Computer Communications.

[5]  Marta M. B. Pascoal,et al.  A new implementation of Yen’s ranking loopless paths algorithm , 2003, 4OR.

[6]  Albert G. Greenberg,et al.  The cost of a cloud: research problems in data center networks , 2008, CCRV.

[7]  Michael Sirivianos,et al.  Inter-datacenter bulk transfers with netstitcher , 2011, SIGCOMM.

[8]  Ilias Giechaskiel,et al.  Delay Tolerant Bulk Data Transfers on the Internet , 2014 .

[9]  ERNEST L. HALL,et al.  Generation of Products and Quotients Using Approximate Binary Logarithms for Digital Filtering Applications , 1970, IEEE Transactions on Computers.

[10]  Laurent Massoulié,et al.  Bandwidth sharing: objectives and algorithms , 2002, TNET.

[11]  Ajay Mahimkar,et al.  Bandwidth on demand for inter-data center communication , 2011, HotNets-X.

[12]  Srikanth Kandula,et al.  Calendaring for wide area networks , 2015, SIGCOMM 2015.

[13]  Hitesh Ballani,et al.  Towards predictable datacenter networks , 2011, SIGCOMM 2011.

[14]  Ratul Mahajan,et al.  On consistent updates in software defined networks , 2013, HotNets.

[15]  David Walker,et al.  Incremental consistent updates , 2013, HotSDN '13.

[16]  Wei Sun,et al.  End-to-end delay bounds for traffic aggregates under guaranteed-rate scheduling algorithms , 2005, IEEE/ACM Transactions on Networking.

[17]  David A. Maltz,et al.  Latency inflation with MPLS-based traffic engineering , 2011, IMC '11.

[18]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks: the single-node case , 1993, TNET.

[19]  Sanjeev Kumar,et al.  Finding a Needle in Haystack: Facebook's Photo Storage , 2010, OSDI.

[20]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[21]  Min Zhu,et al.  B4: experience with a globally-deployed software defined wan , 2013, SIGCOMM.

[22]  Srikanth Kandula,et al.  Achieving high utilization using software-driven WAN (extended version) , 2013 .

[23]  Dritan Nace,et al.  Max-min fairness and its applications to routing and load-balancing in communication networks: a tutorial , 2008, IEEE Communications Surveys & Tutorials.

[24]  James Roberts.  The Cloud is the future Internet: how can we engineer a cloud? , 2013 .