On the Impact of TCP and Per-Flow Scheduling on Internet Performance

Internet performance is tightly related to the properties of TCP and UDP protocols, jointly responsible for the delivery of the great majority of Internet traffic. It is well understood how these protocols behave under first-in-first-out (FIFO) queuing and what are the network congestion effects. However, no comprehensive analysis is available when flow-aware mechanisms such as per-flow scheduling and dropping policies are deployed. Previous simulation and experimental results leave a number of unanswered questions. In this paper, we tackle this issue by modeling via a set of fluid nonlinear ordinary differential equations (ODEs) the instantaneous throughput and the buffer occupancy of long-lived TCP sources under three per-flow scheduling disciplines (Fair Queuing, Longest Queue First, Shortest Queue First) and with longest queue drop buffer management. We study the system evolution and analytically characterize the stationary regime: Closed-form expressions are derived for the stationary throughput/sending rate and buffer occupancy, which give a thorough understanding of short/long-term fairness for TCP traffic. Similarly, we provide the characterization of the loss rate experienced by UDP flows in the presence of TCP traffic. As a result, the analysis allows to quantify benefits and drawbacks related to the deployment of flow-aware scheduling mechanisms in different networking contexts. The model accuracy is confirmed by a set of simulations and by the evaluation of the three scheduling disciplines in a real implementation in the Linux kernel.

[1]  Isaac Keslassy,et al.  Modeling the interactions of congestion control and switch scheduling , 2009, 2009 17th International Workshop on Quality of Service.

[2]  Giorgio Ventre,et al.  Network Simulator NS2 , 2008 .

[3]  T. V. Lakshman,et al.  Design considerations for supporting TCP with per-flow queueing , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

[4]  François Baccelli,et al.  Proxy Caching in Split TCP: Dynamics, Stability and Tail Asymptotics , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[5]  R. Srikant,et al.  Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet , 2006, IEEE/ACM Transactions on Networking.

[6]  John Doyle,et al.  Analysis of nonlinear delay differential equation models of TCP/AQM protocols using sums of squares , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[7]  Marco Ajmone Marsan,et al.  Using partial differential equations to model TCP mice and elephants in large IP networks , 2004, IEEE INFOCOM 2004.

[8]  Jean C. Walrand,et al.  Achieving 100% throughput in an input-queued switch , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[9]  Guillaume Urvoy-Keller.  Institut Eurécom Service Differentiation by Means of Packet Scheduling , .

[10]  Thomas Bonald,et al.  Self-Prioritization of Audio and Video Traffic , 2011, 2011 IEEE International Conference on Communications (ICC).

[11]  Gaurav Raina,et al.  Local bifurcation analysis of some dual congestion control algorithms , 2005, IEEE Transactions on Automatic Control.

[12]  Ananth Balashankar.  Software Defined Networking , 2022 .

[13]  Hossam S. Hassanein,et al.  A performance comparison of class-based scheduling algorithms in future UMTS access , 2005, PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, 2005..

[14]  George Varghese,et al.  Efficient fair queueing using deficit round robin , 1995, SIGCOMM '95.

[15]  Giovanna Carofiglio,et al.  On the Impact of TCP and Per-Flow Scheduling on Internet Performance , 2010, 2010 Proceedings IEEE INFOCOM.

[16]  Donald F. Towsley,et al.  Part II: control theory for buffer sizing , 2005, CCRV.

[17]  Isaac Keslassy,et al.  Modeling the interactions of congestion control and switch scheduling , 2011, Comput. Networks.

[18]  Thomas Voice,et al.  Stability and fairness of explicit congestion control with small buffers , 2008, CCRV.

[19]  A. Kortebi,et al.  On the Scalability of Fair Queueing , 2004 .

[20]  Scott Shenker,et al.  Approximate fairness through differential dropping , 2003, CCRV.

[21]  E. Leonardi,et al.  On the behavior of optimal scheduling algorithms under TCP sources , 2006, 2006 International Zurich Seminar on Communications.

[22]  François Baccelli,et al.  AIMD, fairness and fractal scaling of TCP traffic , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[23]  A. Kortebi,et al.  Cross-protect: implicit service differentiation and admission control , 2004, 2004 Workshop on High Performance Switching and Routing, 2004. HPSR..

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

[25]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

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

[27]  Donald F. Towsley,et al.  Modeling TCP throughput: a simple model and its empirical validation , 1998, SIGCOMM '98.

[28]  John V. Guttag,et al.  Time-based Fairness Improves Performance in Multi-Rate WLANs , 2004, USENIX Annual Technical Conference, General Track.

[29]  Eitan Altman,et al.  TCP in presence of bursty losses , 2000, SIGMETRICS '00.

[30]  Abdesselem Kortebi,et al.  Minimizing the overhead in implementing flow-aware networking , 2005, 2005 Symposium on Architectures for Networking and Communications Systems (ANCS).

[31]  Robert Tappan Morris,et al.  Dynamics of random early detection , 1997, SIGCOMM '97.

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

[33]  Abdesselem Kortebi,et al.  Evaluating the number of active flows in a scheduler realizing fair statistical bandwidth sharing , 2005, SIGMETRICS '05.