TCP throughput and timeout - steady state and time-varying dynamics

While many models of TCP's dynamics have been developed, few focus on the effects of timeout and high loss probability. Active queue management (AQM) is an important application of these dynamic models. However, recent work has shown that AQM provides little performance benefit over drop-tail queueing for HTTP traffic, except, possibly, at high utilizations. It is at these utilizations that the dynamic models of TCP are the least accurate. The paper presents a dynamic model of TCP that accurately models timeout. This model is also applicable to the static case. The paper also presents a model of the variance and the distribution of the congestion window. It is shown that, while the dynamics of the mean value of the congestion window are rather mild, the dynamics of timeout display large oscillations that take several seconds to decay. These oscillations cause the average bit-rate also to oscillate wildly. The paper includes results from several million simulations providing a detailed view of the dynamics of timeout.

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

[2]  Matthew Mathis,et al.  The macroscopic behavior of the TCP congestion avoidance algorithm , 1997, CCRV.

[3]  Donald F. Towsley,et al.  On designing improved controllers for AQM routers supporting TCP flows , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[4]  Jörg Widmer,et al.  TCP Friendly Rate Control (TFRC): Protocol Specification , 2003, RFC.

[5]  Kevin Jeffay,et al.  The effects of active queue management on web performance , 2003, SIGCOMM '03.

[6]  Stefan Savage,et al.  Modeling TCP latency , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[7]  Christophe Diot,et al.  Reasons not to deploy RED , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[8]  Biplab Sikdar,et al.  Analytic models for the latency and steady-state throughput of TCP tahoe, Reno, and SACK , 2003, TNET.

[9]  Stephan Bohacek,et al.  A stochastic model of TCP and fair video transmission , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

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

[11]  G.R. Arce,et al.  Signal processing challenges in active queue management , 2004, IEEE Signal Processing Magazine.

[12]  R. D. van der Mei,et al.  Generalized Processor Sharing Performance Models for Internet Access Lines , 2001 .

[13]  R. Srikant,et al.  Analysis and design of an adaptive virtual queue (AVQ) algorithm for active queue management , 2001, SIGCOMM '01.

[14]  Vishal Misray,et al.  Stochastic Differential Equation Modeling and Analysis of TCP-Windowsize Behavior , 2005 .