YATES: Rapid Prototyping for Traffic Engineering Systems

This paper presents the design and implementation of Yates, a software framework that seeks to dramatically lower the cost of experimenting with different traffic engineering approaches. Yates offers a suite of tools that make it possible to rapidly prototype and evaluate the performance of traffic engineering systems including tools for modeling topologies, routing schemes, demands, prediction algorithms, and failures. Yates comes with two backends: a network simulator that calculates congestion, throughput, loss, latency, etc., and an SDN-based implementation that can be used to validate results obtained via simulation and also provides an easy path to deployment. We evaluate Yates by prototyping 17 TE systems of varying complexity.

[1]  Jianping Wu,et al.  Making intra-domain traffic engineering resistant to failures , 2013, SIGCOMM.

[2]  Sanjeev Arora,et al.  The Multiplicative Weights Update Method: a Meta-Algorithm and Applications , 2012, Theory Comput..

[3]  David E. Culler,et al.  PlanetLab: an overlay testbed for broad-coverage services , 2003, CCRV.

[4]  George F. Riley,et al.  The Georgia Tech Network Simulator , 2003, MoMeTools '03.

[5]  Vishal Misra,et al.  Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED , 2000, SIGCOMM.

[6]  Panagiotis Papadimitratos,et al.  TraNS: realistic joint traffic and network simulator for VANETs , 2008, MOCO.

[7]  Nick McKeown,et al.  A network in a laptop: rapid prototyping for software-defined networks , 2010, Hotnets-IX.

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

[9]  Pierre Schaus,et al.  REPETITA: Repeatable Experiments for Performance Evaluation of Traffic-Engineering Algorithms , 2017, ArXiv.

[10]  Mikkel Thorup,et al.  Internet traffic engineering by optimizing OSPF weights , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[11]  Éva Tardos,et al.  Fast Approximation Algorithms for Fractional Packing and Covering Problems , 1995, Math. Oper. Res..

[12]  David Johnson,et al.  Network architecture for joint failure recovery and traffic engineering , 2011, SIGMETRICS '11.

[13]  Matthew Roughan,et al.  The Internet Topology Zoo , 2011, IEEE Journal on Selected Areas in Communications.

[14]  J. Rexford,et al.  NetScope: Tra c Engineering for IP Networks , 1999 .

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

[16]  Srikanth Kandula,et al.  Traffic engineering with forward fault correction , 2015, SIGCOMM 2015.

[17]  Alia Atlas,et al.  Fast Reroute Extensions to RSVP-TE for LSP Tunnels , 2005, RFC.

[18]  Harald Räcke,et al.  Optimal hierarchical decompositions for congestion minimization in networks , 2008, STOC.

[19]  Jochen Könemann,et al.  Faster and Simpler Algorithms for Multicommodity Flow and Other Fractional Packing Problems , 2007, SIAM J. Comput..

[20]  Mohit Tawarmalani,et al.  Robust Validation of Network Designs under Uncertain Demands and Failures , 2017, NSDI.

[21]  Alexandra Silva,et al.  Probabilistic NetKAT , 2016, ESOP.

[22]  Srinivasan Keshav,et al.  REAL: A Network Simulator , 1988 .

[23]  J. Rexford,et al.  Network architecture for joint failure recovery and traffic engineering , 2011, PERV.

[24]  Arjun Singh,et al.  A practical algorithm for balancing the max-min fairness and throughput objectives in traffic engineering , 2012, 2012 Proceedings IEEE INFOCOM.

[25]  Debasis Mitra,et al.  A case study of multiservice, multipriority traffic engineering design for data networks , 1999, Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042).

[26]  Anja Feldmann,et al.  NetScope: traffic engineering for IP networks , 2000, IEEE Netw..

[27]  Teerawat Issariyakul,et al.  Introduction to Network Simulator NS2 , 2008 .

[28]  Mike Hibler,et al.  An integrated experimental environment for distributed systems and networks , 2002, OPSR.

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

[30]  Deborah Estrin,et al.  Advances in network simulation , 2000, Computer.

[31]  Robert Soulé,et al.  Semi-Oblivious Traffic Engineering: The Road Not Taken , 2018, NSDI.

[32]  Albert G. Greenberg,et al.  Experience in measuring backbone traffic variability: models, metrics, measurements and meaning , 2002, IMW '02.

[33]  Leslie G. Valiant,et al.  A Scheme for Fast Parallel Communication , 1982, SIAM J. Comput..

[34]  Robert Soulé,et al.  Semi-Oblivious Traffic Engineering with SMORE , 2018, ANRW.

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

[36]  Mikkel Thorup,et al.  Traffic engineering with traditional IP routing protocols , 2002, IEEE Commun. Mag..

[37]  Ratul Mahajan,et al.  Measuring ISP topologies with Rocketfuel , 2004, IEEE/ACM Transactions on Networking.

[38]  A. Varga,et al.  THE OMNET++ DISCRETE EVENT SIMULATION SYSTEM , 2003 .

[39]  Xinjie Chang.  Network simulations with OPNET , 1999, WSC'99. 1999 Winter Simulation Conference Proceedings. 'Simulation - A Bridge to the Future' (Cat. No.99CH37038).

[40]  Srikanth Kandula,et al.  Walking the tightrope: responsive yet stable traffic engineering , 2005, SIGCOMM '05.

[41]  Lionel M. Ni,et al.  Traffic engineering with MPLS in the Internet , 2000, IEEE Netw..

[42]  Thomas R. Henderson,et al.  Network Simulations with the ns-3 Simulator , 2008 .

[43]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008, Proceedings of the Python in Science Conference.