Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-03T05:22:14.405Z Has data issue: false hasContentIssue false

STOCHASTIC DIFFERENTIAL EQUATION FOR TCP WINDOW SIZE: ANALYSIS AND EXPERIMENTAL VALIDATION

Published online by Cambridge University Press:  22 January 2004

A. Budhiraja
Affiliation:
Department of Statistics, University of North Carolina, Chapel Hill, NC 27599
F. Hernández-Campos
Affiliation:
Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599
V. G. Kulkarni
Affiliation:
Department of Operations Research, University of North Carolina, Chapel Hill, NC 27599, E-mail: [email protected]
F. D. Smith
Affiliation:
Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599

Abstract

In this paper we develop a stochastic differential equation to describe the dynamic evolution of the congestion window size of a single TCP session over a network. The model takes into account recovery from packet losses with both fast recovery and time-outs, boundary behavior at zero and maximum window size, and slow-start after time-outs. We solve the differential equation to derive the distribution of the window size in steady state. We compare the model predictions with the output from the NS simulator.

Type
Research Article
Copyright
© 2004 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Abouzeid, A., Roy, S., & Azizoglu, M. (2000). Stochastic modeling of TCP over lossy links. Proceedings of INFOCOM 2000.CrossRef
Abouzeid, A. Roy, S.,, &Azizoglu, M. (1999). Stochastic modeling of TCP over random loss channels. Proceedings of the 6th International Conference on High Performance Computing.CrossRef
Altman, E., Avrachenkov, K., & Barakat, C. (2000). A stochastic model of TCP/IP with stationary random loss. Proceedings of SIGCOMM 2000.
Altman, E., Avrachenkov, K., & Barakat, C. (2000). Impact of bursty losses on TCP performance. Performance Evaluation 42(2–3): 129147.Google Scholar
Altman, E., Avrachenkov, K., & Barakat, C. (2000). TCP in presence of bursty losses. Proceedings of SIGMETRICS 2000.CrossRef
Altman, E., Avrachenkov, K., & Barakat, C. (2002). TCP network calculus: The case of large delay–bandwidth product. Proceedings of INFOCOM 2002.CrossRef
Altman, E., Jimenez, T., & Nunez-Queija, R. (2002). Analysis of two competing TCP/IP connections. Performance Evaluation 49(1–4): 4355.Google Scholar
Anjum, F. & Tassiulas, L. (1999). On the behavior of different TCP algorithms over a wireless channel with correlated packet losses. Proceedings of SIGMETRICS 1999.CrossRef
Baccelli, F. & Hong, D. (2000). TCP is max-plus linear. Proceedings of SIGCOMM 2000.
Baccelli, F. & Hong, D. (2002). AIMD, fairness and fractal scaling of TCP traffic. Proceedings of INFOCOM 2002.CrossRef
Barakat, C. (2001). TCP modeling and validation. IEEE Network 15(3): 3847.Google Scholar
Breslau, L., Estrin, D., Fall, K., Floyd, S., Heidemann, J., Helmy, A., Huang, P., McCanne, S., Varad-han, K., Xu, Y., & Yu, H. (2000). Advances in network simulation. IEEE Computer 33(5): 5967.Google Scholar
Cardwell, N., Savage, S., & Anderson, T. (2000). Modeling TCP latency. Proceedings of INFOCOM 2000.CrossRef
Dumas, V., Guillemin, F., & Robert, P. (2001). Limit results for Markovian models of TCP. Proceedings of GLOBECOM 2001.
Dumas, V., Guillemin, F., & Robert, P. (2002). A Markovian analysis of additive-increase multiplicative-decrease (AIMD) algorithms. Advances in Applied Probability 34(1): 85111.Google Scholar
Feldmann, A., Gilbert, A., Huang, P., & Willinger, W. (1999). Dynamics of IP traffic: A study of the role of variability and the impact of control. Proceedings of SIGCOMM 1999.CrossRef
Floyd, S. (1991). Connections with multiple congested gateways in packet-switched networks Part 1: One-way traffic. Computer Communication Review 21(5): 3047.Google Scholar
Floyd, S. & Fall, K. (1999). Promoting the use of end-to-end congestion control in the internet. IEEE/ACM Transactions on Networking 7(4): 458472.Google Scholar
Floyd, S., Handley, M., Padhye, J., & Widmer, J. (2000). Equation-based congestion control for unicast applications. Proceedings of SIGCOMM 2000.CrossRef
Floyd, S. & Jacobson, V. (1992). On traffic phase effects in packet-switched gateways. Internetworking: Research and Experience 3(3): 115156.Google Scholar
Garetto, M., Cigno, R., Meo, M., & Marsan, M. (2001). A detailed and accurate closed queueing network model of many interacting TCP flows. Proceedings of INFOCOM 2001.
Goyal, M., Guérin, R., & Rajan, R. (2002). Predicting TCP throughput from non-invasive network sampling. Proceedings of INFOCOM 2002.CrossRef
Hollot, C., Misra, V., Towsley, D., & Gong, W. (2001). A control theoretic analysis of RED. Proceedings of INFOCOM 2001.CrossRef
Hollot, C., Misra, V., Towsley, D., & Gong, W. (2001). On designing improved controllers for AQM routers supporting TCP flows. Proceedings of INFOCOM 2001.
Kelly, F., Maulloo, A., & Tan, D. (1998). Rate control for communication networks: Shadow prices, proportional fairness and stability. Journal of the Operational Research Society 49(3): 237252.Google Scholar
Kumar, A. (1998). Comparative performance analysis of versions of TCP in local network with a lossy link. IEEE/ACM Transactions on Networking 6(4): 485498.Google Scholar
Lakshman, T.V. & Madhow, U. (1997). The performance of networks with high bandwidth-delay products and random loss. IEEE/ACM Transactions on Networking 5(3): 336350.Google Scholar
Lakshman, T.V., Madhow, U., & Suter, B. (1997). Window-based error recovery and flow control with a slow acknowledgment channel: A study of TCP/IP performance. Proceedings of INFOCOM 1997.
Lakshman, T.V., Madhow, U., & Suter, B. (2000). TCP/IP performance with random loss and bidirectional congestion. IEEE/ACM Transactions on Networking 8(5): 541555.Google Scholar
Low, S.H. (2000). A duality model of TCP and queue management algorithms. Extended version of paper presented at Proceedings of ITC Specialist Seminar on IP Traffic Measurement, Modeling and Management.
Low, S., Peterson, L., & Wang, L. (2001). Understanding TCP Vegas: A duality model. Proceedings of SIGMETRICS 2001.CrossRef
Mathis, M., Semke, J., Mahdavi, J., & Ott, T. (1997). The macroscopic behavior of the TCP congestion avoidance algorithm. Computer Communication Review 27(3): 6782.Google Scholar
Misra, A. & Ott, T. (1999). The window distribution of idealized TCP congestion avoidance with variable packet loss. Proceedings of INFOCOM 1999.
Misra, V., Gong, W., & Towsley, D. (1999). Stochastic differential equation modeling and analysis of TCP window size behavior. Proceedings of Performance 1999.
Misra, V., Gong, W., & Towsley, D. (2000). A fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED. Proceedings of SIGCOMM 2000.
Mitzenmacher, M. & Rajaraman, R. (2001). Towards more complete models of TCP latency and throughput. Journal of Supercomputing 20(2): 137160.Google Scholar
Ott, T., Kemperman, J.H.B., & Mathis, M. (1996). The stationary behavior of ideal TCP congestion avoidance, unpublished manuscript.
Padhye, J., Firoiu, V., Towsley, D., & Kurose, J. (1998). Modeling TCP throughput: A simple model and its empirical validation. Proceedings of SIGCOMM 1998.
Padhye, J., Firoiu, V., Towsley, D., & Kurose, J. (2000). Modeling TCP Reno performance: A simple model and its empirical validation. IEEE/ACM Transactions on Networking 8(2): 133145.Google Scholar
Roughan, M., Erramilli, A., & Veitch, D. (2001). Network performance for TCP networks. Part 1: Persistent sources. Proceedings of Seventeenth International Teletraffic Congress.
Sahu, S., Nain, P., Towsley, D., Diot, C., & Firoiu, V. (2000). On achievable service differentiation with token bucket marking for TCP. Proceedings of SIGMETRICS 2000.CrossRef
Savari, S. & Telatar, E. (1999). The behavior of stochastic processes arising in window protocols. Proceedings of the 1999 IEEE International Symposium on Information Theory.
Schwefel, H. (2001). Behavior of TCP-like elastic traffic at a buffered bottleneck router. Proceedings of INFOCOM 2001.
Sikdar, B., Kalyanaraman, S., & Vastola, K.S. (2001). An integrated model for the latency and steady-state throughput of TCP connections. Performance Evaluation 46(2–3): 139154.Google Scholar
Sikdar, B., Kalyanaraman, S., & Vastola, K.S. (2001). Analytic models and comparative study of the latency and steady-state throughput of TCP Tahoe, Reno and SACK. Proceedings of GLOBECOM 2001.
Willinger, W., Taqqu, N., Sherman, R., & Wilson, D. (1997). Self-similarity through high-variability: Statistical analysis of Ethernet LAN traffic at the source level. IEEE/ACM Transactions on Networking 5(1): 7186.Google Scholar
Yang, Y. & Lam, S. (2000). General AIMD congestion control. Proceedings of ICNP 2000.CrossRef
Yang, Y., Kim, M., & Lam, S. (2001). Transient behaviors of TCP-friendly congestion control protocols. Proceedings of INFOCOM 2001.
Zorzi, M., Chockalingam, A., & Rao, R. (2000). Performance analysis of TCP on channels with memory. IEEE-JSAC 18: 12891300.Google Scholar
URL: http://www.cs.unc.edu/Research/dirt/proj/tcpmodel