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PI2: A Linearized AQM for both Classic and Scalable TCP

Published: 06 December 2016 Publication History
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  • Abstract

    This paper concerns the use of Active Queue Management (AQM) to reduce queuing delay. It offers insight into why it has proved hard for a Proportional Integral (PI) controller to remain both responsive and stable while controlling `Classic' TCP flows, such as TCP Reno and Cubic. Due to their non-linearity, the controller's adjustments have to be smaller when the target drop probability is lower. The PI Enhanced (PIE) algorithm attempts to solve this problem by scaling down the adjustments of the controller using a look-up table. Instead, we control an internal variable that is by definition linearly proportional to the load, then post-process it into the required Classic drop probability---in fact we show that the output simply needs to be squared. This allows tighter control, giving responsiveness and stability better or no worse than PIE achieves, but without all its corrective heuristics.
    Additionally, with suitable packet classification, it becomes simple to extend this PI2 AQM to support coexistence between Classic and Scalable congestion controls in the public Internet. Unlike a Classic congestion control, a Scalable congestion control ensures sufficient feedback at any flow rate, an example being Data Centre TCP (DCTCP). A Scalable control is linear, so we can use the internal variable directly without any squaring, by omitting the post-processing stage.
    We implemented this PI2 AQM as a Linux qdisc to extensively test our claims using Classic and Scalable TCPs.

    References

    [1]
    R. Adams. Active Queue Management: A Survey. IEEE Communications Surveys & Tutorials, 15(3):1425--1476, 2013.
    [2]
    M. Alizadeh, A. Greenberg, D. A. Maltz, J. Padhye, P. Patel, B. Prabhakar, S. Sengupta, and M. Sridharan. Data Center TCP (DCTCP). Proc. ACM SIGCOMM'10, Computer Communication Review, 40(4):63--74, Oct. 2010.
    [3]
    M. Alizadeh, A. Javanmard, and B. Prabhakar. Analysis of DCTCP: Stability, Convergence, and Fairness. In Proceedings of the ACM SIGMETRICS Joint International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS '11, pages 73--84, New York, NY, USA, 2011. ACM.
    [4]
    D. Black. Explicit Congestion Notification (ECN) Experimentation. Internet Draft draft-black-tsvwg-ecn-experimentation-00, Internet Engineering Task Force, Sept. 2016. (Work in Progress).
    [5]
    O. Bondarenko, K. De Schepper, I.-J. Tsang, B. Briscoe, A. Petlund, and C. Griwodz. Ultra-Low Delay for All: Live Experience, Live Analysis. In Proc. ACM Multimedia Systems; Demo Session, pages 33:1--33:4. ACM, May 2016.
    [6]
    B. Briscoe. Review: Proportional Integral controller Enhanced (PIE) Active Queue Management (AQM). Technical Report TR-TUB8--2015-001, BT, May 2015.
    [7]
    B. Briscoe, A. Brunstrom, A. Petlund, D. Hayes, D. Ros, I.-J. Tsang, S. Gjessing, G. Fairhurst, C. Griwodz, and M. Welzl. Reducing Internet Latency: A Survey of Techniques and their Merits. IEEE Communications Surveys & Tutorials, 18(3):2149--2196, 2016.
    [8]
    B. Briscoe (Ed.), K. De Schepper, and M. Bagnulo. Low Latency, Low Loss, Scalable Throughput (L4S) Internet Service: Problem Statement. Internet Draft draft-briscoe-tsvwg-aqm-tcpm-rmcat-l4s-problem-02, Internet Engineering Task Force, July 2016. (Work in Progress).
    [9]
    CableLabs. Data-Over-Cable Service Interface Specifications DOCSIS® 3.1; MAC and Upper Layer Protocols Interface Specification. Specification CM-SP-MULPIv3.1-I01--131029, CableLabs, Oct. 2013.
    [10]
    Y. Choi, J. A. Silvester, and H.-c. Kim. Analyzing and Modeling Workload Characteristics in a Multiservice IP Network. Internet Computing, IEEE, 15(2):35--42, March 2011.
    [11]
    K. De Schepper and O. Bondarenko. Linux sch\_pi2 qdisc source code available at https://github.com/olgabo/dualpi2, June 2016.
    [12]
    K. De Schepper, O. Bondarenko, I.-J. Tsang, and B. Briscoe. 'Data Centre to the Home': Deployable Ultra-Low Queuing Delay for All. Sept. 2016. (Under Submission).
    [13]
    K. De Schepper, B. Briscoe (Ed.), O. Bondarenko, and I.-J. Tsang. DualQ Coupled AQM for Low Latency, Low Loss and Scalable Throughput. Internet Draft draft-briscoe-aqm-dualq-coupled-01, Internet Engineering Task Force, Mar. 2016. (Work in Progress).
    [14]
    K. De Schepper, B. Briscoe (Ed.), and I.-J. Tsang. Identifying Modified Explicit Congestion Notification (ECN) Semantics for Ultra-Low Queuing Delay. Internet Draft draft-briscoe-tsvwg-ecn-l4s-id-01, Internet Engineering Task Force, Mar. 2016. (Work in Progress).
    [15]
    N. Finn (Ed.). IEEE Standard for Local and Metropolitan Area Networks--Virtual Bridged Local Area Networks - Amendment: 10: Congestion Notification. Standard 802.1Qau, IEEE, Apr. 2010.
    [16]
    S. Ha, I. Rhee, and L. Xu. CUBIC: a new TCP-friendly high-speed TCP variant. SIGOPS Operating Systems Review, 42(5):64--74, July 2008.
    [17]
    O. Hohlfeld, E. Pujol, F. Ciucu, A. Feldmann, and P. Barford. A QoE Perspective on Sizing Network Buffers. In Proc. Internet Measurement Conf (IMC'14), pages 333--346. ACM, Nov. 2014.
    [18]
    C. V. Hollot, V. Misra, D. Towsley, and W. Gong. Analysis and design of controllers for AQM routers supporting TCP flows. IEEE Transactions on Automatic Control, 47(6):945--959, Jun 2002.
    [19]
    C. V. Hollot, V. Misra, D. F. Towsley, and W. Gong. A Control Theoretic Analysis of RED. In Proc. INFOCOM 2001. 20th Annual Joint Conf. of the IEEE Computer and Communications Societies., volume 3, pages 1510--19, 2001.
    [20]
    Y. Hong and O. W. W. Yang. Self-tuning TCP traffic controller using gain margin specification. IET Communications, 1(1):27--33, February 2007.
    [21]
    Y. Hong, O. W. W. Yang, and C. Huang. Self-tuning PI TCP flow controller for AQM routers with interval gain and phase margin assignment. In Global Telecommunications Conference (Globecom'04), volume 3, pages 1324--1328, 2004.
    [22]
    S. Irteza, A. Ahmed, S. Farrukh, B. Memon, and I. Qazi. On the Coexistence of Transport Protocols in Data Centers. In Proc. IEEE Int'l Conf. on Communications (ICC 2014), pages 3203--3208, June 2014.
    [23]
    M. Kühlewind, D. P. Wagner, J. M. R. Espinosa, and B. Briscoe. Using Data Center TCP (DCTCP) in the Internet. In Proc. Third IEEE Globecom Workshop on Telecommunications Standards: From Research to Standards, pages 583--588, Dec. 2014.
    [24]
    M. Kwon and S. Fahmy. A Comparison of Load-based and Queue-based Active Queue Management Algorithms. In Proc. Int'l Soc. for Optical Engineering (SPIE), volume 4866, pages 35--46, 2002.
    [25]
    M. Mathis, J. Semke, J. Mahdavi, and T. Ott. The macroscopic behavior of the TCP Congestion Avoidance algorithm. Computer Communication Review, 27(3), July 1997.
    [26]
    V. Misra, W.-B. Gong, and D. Towsley. Fluid-based Analysis of a Network of AQM Routers Supporting TCP Flows with an Application to RED. SIGCOMM Computer Comms. Review, 30(4):151--160, Aug. 2000.
    [27]
    K. Nichols and V. Jacobson. Controlling queue delay. ACM Queue, 10(5), May 2012.
    [28]
    R. Pan et al. PIE: A lightweight control scheme to address the bufferbloat problem. In Proc. IEEE Int'l Conf. on High Performance Switching and Routing (HPSR), pages 148--155, 2013.
    [29]
    R. Pan, P. Natarajan, F. Baker, G. White, B. Ver Steeg, M. Prabhu, C. Piglione, and V. Subramanian. PIE: A Lightweight Control Scheme To Address the Bufferbloat Problem. Internet Draft draft-ietf-aqm-pie-10, Internet Engineering Task Force, Sept. 2016. (Work in progress).
    [30]
    K. K. Ramakrishnan, S. Floyd, and D. Black. The Addition of Explicit Congestion Notification (ECN) to IP. Request for Comments RFC 3168, RFC Editor, Sept. 2001.
    [31]
    M. Sågfors, R. Ludwig, M. Meyer, and J. Peisa. Buffer Management for Rate-Varying 3G Wireless Links Supporting TCP Traffic. In Proc Vehicular Technology Conference, Apr. 2003.
    [32]
    G. White. Active Queue Management Algorithms for DOCSIS 3.0; A Simulation Study of CoDel, SFQ-CoDel and PIE in DOCSIS 3.0 Networks. Technical report, CableLabs, Apr. 2013.

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    cover image ACM Conferences
    CoNEXT '16: Proceedings of the 12th International on Conference on emerging Networking EXperiments and Technologies
    December 2016
    524 pages
    ISBN:9781450342926
    DOI:10.1145/2999572
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 06 December 2016

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    Author Tags

    1. algorithms
    2. aqm
    3. congestion control
    4. fairness
    5. latency
    6. qos
    7. scalability
    8. scheduling
    9. starvation
    10. tcp
    11. testbed evaluation

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    CoNEXT '16 Paper Acceptance Rate 30 of 160 submissions, 19%;
    Overall Acceptance Rate 198 of 789 submissions, 25%

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    • (2022)Active Queue Management on the Tofino programmable switch: The (Dual)PI2 caseICC 2022 - IEEE International Conference on Communications10.1109/ICC45855.2022.9838674(1685-1691)Online publication date: 16-May-2022
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