ABSTRACT
The effects of data center traffic characteristics on data center traffic engineering is not well understood. In particular, it is unclear how existing traffic engineering techniques perform under various traffic patterns, namely how do the computed routes differ from the optimal routes. Our study reveals that existing traffic engineering techniques perform 15% to 20% worse than the optimal solution. We find that these techniques suffer mainly due to their inability to utilize global knowledge about flow characteristics and make coordinated decision for scheduling flows.
To this end, we have developed MicroTE, a system that adapts to traffic variations by leveraging the short term and partial predictability of the traffic matrix. We implement MicroTE within the OpenFlow framework and with minor modification to the end hosts. In our evaluations, we show that our system performs close to the optimal solution and imposes minimal overhead on the network making it appropriate for current and future data centers.
- M. Al-Fares, A. Loukissas, and A. Vahdat. A scalable, commodity data center network architecture. SIGCOMM '08, New York, NY, USA, 2008. ACM. Google ScholarDigital Library
- M. Al-Fares, S. Radhakrishnan, B. Raghavan, N. Huang, and A. Vahdat. Hedera: Dynamic flow scheduling for data center networks. In NSDI '10. Google ScholarDigital Library
- Y. Azar, E. Cohen, A. Fiat, H. Kaplan, and H. Racke. Optimal oblivious routing in polynomial time. STOC '03. Google ScholarDigital Library
- B. Fortz and M. Thorup. Internet Traffic Engineering by Optimizing OSPF Weights. In Infocom, 2000.Google ScholarCross Ref
- T. Benson, A. Akella, and D. Maltz. Network Traffic Characteristics of Data Centers in the Wild. In Proceedings of IMC, 2010. Google ScholarDigital Library
- T. Benson, A. Anand, A. Akella, and M. Zhang. Understanding Data Center Traffic Characteristics. In Proceedings of Sigcomm Workshop: Research on Enterprise Networks, 2009. Google ScholarDigital Library
- A. Elwalid, C. Jin, S. Low, and I. Widjaja. Mate: multipath adaptive traffic engineering. Comput. Netw., 40:695--709, December 2002. Google ScholarDigital Library
- N. Farrington, G. Porter, S. Radhakrishnan, H. H. Bazzaz, V. Subramanya, Y. Fainman, G. Papen, and A. Vahdat. Helios: a hybrid electrical/optical switch architecture for modular data centers. SIGCOMM '10, NY, USA, 2010. Google ScholarDigital Library
- A. Greenberg, J. R. Hamilton, N. Jain, S. Kandula, C. Kim, P. Lahiri, D. A. Maltz, P. Patel, and S. Sengupta. V12: a scalable and flexible data center network. In SIGCOMM, 2009. Google ScholarDigital Library
- C. Guo, H. Wu, K. Tan, L. Shi, Y. Zhang, and S. Lu. Dcell: a scalable and fault-tolerant network structure for data centers. SIGCOMM '08. Google ScholarDigital Library
- S. Kandula, D. Katabi, B. Davie, and A. Charny. Walking the tightrope: responsive yet stable traffic engineering. In SIGCOMM, 2005. Google ScholarDigital Library
- S. Kandula, J. Padhye, and P. Bahl. Flyways to de-congest data center networks. In Proc. ACM Hotnets-VIII, New York City, NY. USA., Oct. 2009.Google Scholar
- S. Kandula, S. Sengupta, A. Greenberg, P. Patel, and R. Chaiken. The Nature of Data Center Traffic: Measurements and Analysis. In IMC, 2009. Google ScholarDigital Library
- N. Mckeown, S. Shenker, T. Anderson, L. Peterson, J. Turner, H. Balakrishnan, and J. Rexford. Openflow: Enabling innovation in campus networks.Google Scholar
- A. Medina, N. Taft, K. Salamatian, S. Bhattacharyya, and C. Diot. Traffic matrix estimation: existing techniques and new directions. SIGCOMM '02. Google ScholarDigital Library
- R. Niranjan Mysore, A. Pamboris, N. Farrington, N. Huang, P. Miri, S. Radhakrishnan, V. Subramanya, and A. Vahdat. Portland: a scalable fault-tolerant layer 2 data center network fabric. In SIGCOMM, 2009. Google ScholarDigital Library
- A. Shieh, S. Kandula, A. Greenberg, C. Kim, and B. Saha. Sharing the data center network. NSDI'11. Google ScholarDigital Library
- A. Tavakoli, M. Casado, T. Koponen, and S. Shenker. Applying nox to the datacenter. In Proc. of (HotNets-VIII), 2009.Google Scholar
- G. Wang, D. G. Andersen, M. Kaminsky, M. Kozuch, T. S. E. Ng, K. Papagiannaki, and M. Ryan. c-Through: Part-time optics in data centers. In Proc. ACM SIGCOMM, New Delhi, India, Aug. 2010. Google ScholarDigital Library
- H. Wang, H. Xie, L. Qiu, Y. R. Yang, Y. Zhang, and A. Greenberg. Cope: traffic engineering in dynamic networks. SIGCOMM Comput. Commun. Rev., 36(4):99--110, 2006. Google ScholarDigital Library
- Y. Zhang, L. Breslau, V. Paxson, and S. Shenker. Traffic Engineering with Estimated Traffic Matrices. Miami, FL, Oct. 2003.Google Scholar
Index Terms
- MicroTE: fine grained traffic engineering for data centers
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