Adaptive Robust Traffic Engineering in Software Defined Networks

One of the key advantages of Software-Defined Networks (SDN) is the opportunity to integrate traffic engineering modules able to optimize network configuration according to traffic. Ideally, the network should be dynamically reconfigured as traffic evolves, so as to achieve remarkable gains in the efficient use of resources with respect to traditional static approaches. Unfortunately, reconfigurations cannot be too frequent due to a number of reasons related to route stability, forwarding rules instantiation, individual flows dynamics, traffic monitoring overhead, etc.In this paper, we focus on the fundamental problem of deciding whether, when and how to reconfigure the network during traffic evolution. We propose a new approach to cluster relevant points in the multi-dimensional traffic space taking into account similarities in optimal routing and not only in traffic values. Moreover, to provide more flexibility to the decisions on when to apply a reconfiguration, we allow some overlap between clusters that can guarantee a good-quality routing regardless of the transition instant.We compare our algorithm with state-of-the-art approaches in realistic network scenarios. Results show that our method significantly reduces the number of reconfigurations with a negligible deviation of the network performance with respect to the continuous update of the network configuration.

[1]  Edith Cohen,et al.  Optimal oblivious routing in polynomial time , 2003, STOC '03.

[2]  Yin Zhang,et al.  Finding critical traffic matrices , 2005, 2005 International Conference on Dependable Systems and Networks (DSN'05).

[3]  Ming Zhang,et al.  MicroTE: fine grained traffic engineering for data centers , 2011, CoNEXT '11.

[4]  Walid Ben-Ameur,et al.  Routing of Uncertain Traffic Demands , 2005 .

[5]  Yixin Chen,et al.  Cupid: Congestion-free consistent data plane update in software defined networks , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[6]  Richard J. La,et al.  Robust Routing with Unknown Traffic Matrices , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[7]  Christoph Albrecht,et al.  Global routing by new approximation algorithms for multicommodityflow , 2001, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[8]  Edith Cohen,et al.  Making intra-domain routing robust to changing and uncertain traffic demands: understanding fundamental tradeoffs , 2003, SIGCOMM '03.

[9]  Jeremie Leguay,et al.  Controlling flow reconfigurations in SDN , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[10]  Federico Larroca,et al.  Robust Routing mechanisms for intradomain Traffic Engineering in dynamic networks , 2009, 2009 Latin American Network Operations and Management Symposium.

[11]  Rui Zhang-Shen,et al.  Valiant Load-Balancing: Building Networks That Can Support All Traffic Matrices , 2010, Algorithms for Next Generation Networks.

[12]  Pedro Casas,et al.  Multi Hour Robust Routing and Fast Load Change Detection for Traffic Engineering , 2008, 2008 IEEE International Conference on Communications.

[13]  Roger Wattenhofer,et al.  On consistent migration of flows in SDNs , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[14]  Sudipta Sengupta,et al.  Efficient and robust routing of highly variable traffic , 2005 .

[15]  Konstantina Papagiannaki,et al.  Structural analysis of network traffic flows , 2004, SIGMETRICS '04/Performance '04.

[16]  Fernando M. V. Ramos,et al.  Software-Defined Networking: A Comprehensive Survey , 2014, Proceedings of the IEEE.

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

[18]  Mikkel Thorup,et al.  Traffic engineering with estimated traffic matrices , 2003, IMC '03.

[19]  Donald F. Towsley,et al.  On optimal routing with multiple traffic matrices , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[20]  Alberto Dainotti,et al.  SWIFT: Predictive Fast Reroute , 2017, SIGCOMM.

[21]  Albert G. Greenberg,et al.  COPE: traffic engineering in dynamic networks , 2006, SIGCOMM.

[22]  Tal Mizrahi,et al.  TimeFlip: Scheduling network updates with timestamp-based TCAM ranges , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[23]  Srikanth Kandula,et al.  Achieving high utilization with software-driven WAN , 2013, SIGCOMM.

[24]  Chen-Nee Chuah,et al.  Intelligent SDN based traffic (de)Aggregation and Measurement Paradigm (iSTAMP) , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[25]  Kazutaka Murakami,et al.  Optimal capacity and flow assignment for self-healing ATM networks based on line and end-to-end restoration , 1998, TNET.

[26]  David Walker,et al.  Consistent updates for software-defined networks: change you can believe in! , 2011, HotNets-X.

[27]  Ning Wang,et al.  An overview of routing optimization for internet traffic engineering , 2008, IEEE Communications Surveys & Tutorials.

[28]  Mateusz Zotkiewicz,et al.  Robust routing and optimal partitioning of a traffic demand polytope , 2011, Int. Trans. Oper. Res..

[29]  Xin Jin,et al.  Dynamic scheduling of network updates , 2014, SIGCOMM.