Pitfalls in the fluid modeling of RTT variations in window-based congestion control

Deterministic delay differential equation models, where the packet traffic is modeled as a fluid, are widely used to study congestion control algorithms in the Internet. In this paper, we point out some pitfalls in such fluid modeling of window flow control algorithms. Specifically, we argue that the modeling assumptions used to capture the variability in the RTT (due to queue length fluctuations) may play a critical role in our ability to design stable algorithms. We study two scenarios to illustrate the dramatic impact of RTT modeling. We first consider TCP-Reno with RED, and show that assuming that the RTT is a constant (when it is actually time-varying) leads to conservative parameter choices, i.e., the system continues to be stable even with variable RTT. On the other hand, for the recently proposed stabilized Vegas, we show the following result: while the network can be stabilized under the constant RTT assumption, there is no choice of parameters that would stabilize the system when the RTT variations are taken into account. Interestingly, such problems do not arise if the congestion-control mechanisms at the end-users are rate-based.

[1]  Steven H. Low,et al.  Stabilized Vegas , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

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

[3]  Richard J. La,et al.  Global stability conditions for rate control with arbitrary communication delays , 2006, IEEE/ACM Transactions on Networking.

[4]  Glenn Vinnicombe,et al.  ON THE STABILITY OF NETWORKS OPERATING TCP-LIKE CONGESTION CONTROL , 2002 .

[5]  QUTdN QeO,et al.  Random early detection gateways for congestion avoidance , 1993, TNET.

[6]  Steven H. Low,et al.  REM: active queue management , 2001, IEEE Netw..

[7]  R. Srikant,et al.  An adaptive virtual queue (AVQ) algorithm for active queue management , 2004, IEEE/ACM Transactions on Networking.

[8]  Ramesh Johari,et al.  End-to-end congestion control for the internet: delays and stability , 2001, TNET.

[9]  Frank Kelly,et al.  Fairness and Stability of End-to-End Congestion Control , 2003, Eur. J. Control.

[10]  Donald F. Towsley,et al.  Analysis and design of controllers for AQM routers supporting TCP flows , 2002, IEEE Trans. Autom. Control..

[11]  C. Desoer,et al.  On the generalized Nyquist stability criterion , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[12]  T. P. Kelly,et al.  On engineering a stable and scalable TCP variant , 2002 .

[13]  M. Arcak,et al.  L/sub p/ stability and delay robustness of network flow control , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[14]  Donald F. Towsley,et al.  A control theoretic analysis of RED , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[15]  R. Srikant,et al.  Exponential-RED: a stabilizing AQM scheme for low- and high-speed TCP protocols , 2005, IEEE/ACM Trans. Netw..

[16]  G. Dullerud,et al.  Global stability of Internet congestion controllers with heterogeneous delays , 2004 .

[17]  R. Srikant,et al.  Robustness of real and virtual queue-based active queue management schemes , 2005, IEEE/ACM Transactions on Networking.

[18]  Larry Peterson,et al.  TCP Vegas: new techniques for congestion detection and avoidance , 1994, SIGCOMM 1994.

[19]  Glenn Vinnicombe,et al.  On the stability of end-to-end congestion control for the internet , 2001 .

[20]  Rayadurgam Srikant,et al.  Controlling the Internet: a survey and some new results , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[21]  Kang G. Shin,et al.  The BLUE active queue management algorithms , 2002, TNET.

[22]  Sally Floyd,et al.  HighSpeed TCP for Large Congestion Windows , 2003, RFC.

[23]  Rayadurgam Srikant,et al.  Analysis and design of an adaptive virtual queue (AVQ) algorithm for active queue management , 2001, SIGCOMM.

[24]  Rayadurgam Srikant,et al.  The Mathematics of Internet Congestion Control , 2003 .

[25]  R. Srikant,et al.  End-to-end congestion control schemes: utility functions, random losses and ECN marks , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[26]  Laurent Massoulié,et al.  Stability of distributed congestion control with heterogeneous feedback delays , 2002, IEEE Trans. Autom. Control..

[27]  Larry L. Peterson,et al.  TCP Vegas: new techniques for congestion detection and avoidance , 1994 .

[28]  Fernando Paganini,et al.  Internet congestion control , 2002 .

[29]  Richard J. La,et al.  Global stability conditions for rate control with arbitrary communication delays , 2004, IEEE/ACM Transactions on Networking.

[30]  Glenn Vinnicombe,et al.  Robust congestion control for the Internet , 2002 .

[31]  Richard J. Gibbens,et al.  Resource pricing and the evolution of congestion control , 1999, at - Automatisierungstechnik.

[32]  Fernando Paganini,et al.  A global stability result in network flow control , 2002, Syst. Control. Lett..

[33]  Frank Kelly,et al.  Mathematical Modelling of the Internet , 2001 .