Stochastic Modeling of the TCP Protocol
PhD Candidacy
Exam Paper List
1. TCP Protocol Specifications
Many TCP variants exist and are distinguished by the particular way the sources react to packet loss events. I will focus on the most-widely used variants, TCP-Tahoe [1], TCP-Reno [2], TCP-NewReno[3], TCP-SACK[4], and TCP-Vegas [5].
2. Renewal Theory Models
Renewal theory based modeling has received a lot of attention in the literature. This approach assumes a single source model and aims to compute TCP’s throughput and latency as a function of the network characteristics. I will give a description of the work (listed in chronology order) in: [6, 7, 8, 9, 10, 11].
3. Fixed Point Methods
In this approach the interaction between separate TCP sources is studied in order to find the operating regime of a network. I will discuss the following papers: [12, 13, 14, 15].
4. Fluid Models
In this
framework TCP packets are app
5. Processor Sharing Models
The processor
sharing framework has been traditionally used to model the interaction between
flows sharing a server. In this model, performance metrics (e.g., download
times and number of concurrent connections) are studied on a flow level, and
the complexities of the TCP protocol are hidden. I will cover the following
papers: [20, 21]
6. Control Theoretic Models
Methods from the mature field of control theory have been successfully applied to TCP-network modeling and the design of flow-control mechanisms. I will briefly cover this area by the following papers: [22, 23].
7. Experimental Enhancement and Future Trends
I will discuss recent
suggestions to enhance or replace TCP, such as [24, 25]; and will present a
methodology to infer and track the key parameters of TCP in large scale
networks such as the internet [26, 27]. Multimedia congestion control,
particularly the idea of TCP-friendliness, represents one of the current trends
in Internet congestion control research. I will discuss some representative
results based on [28, 29].
References
[1] V. Jacobson, “Congestion
avoidance and control,” in ACM SIGCOMM ’88,
[2] M. Allman, V. Paxson, and W. Stevens, “TCP Congestion Control.” RFC 2581, Apr. 1999.
[3] S. Floyd and T. Henderson, “The NewReno Modification to TCP’s Fast Recovery Algorithm,” RFC 2582, Apr. 1999.
[4] M. M. Floyd S., Mahdavi J. and P. M., “An Extension to the Selective Acknowledgement (SACK) Option for TCP,” RFC 2883, July 2000.
[5] L. S. Brakmo and L. L. Peterson, “TCP Vegas: End to end congestion avoidance on a global internet,” IEEE Journal on Selected Areas in Communications, vol. 13, no. 8, pp. 1465–1480, 1995.
[6] M. Mathis, J. Semke, and J. Mahdavi, “The macroscopic behavior of the TCP congestion avoidance algorithm,” Computer Communications Review, vol. 27, no. 3, 1997.
[7] J. Padhye, V. Firoiu, D. Towsley, and J. Kurose, “Modeling TCP throughput: A simple model and its empirical validation,” in ACM SIGCOMM, 1998, pp. 303–314.
[8] A. Kumar, “Comparative performance analysis of versions of TCP in a local network with a lossy link,” IEEE/ACM Transactions on Networking, vol. 6, no. 4, pp. 485–498, 1998.
[9] N. Cardwell, S. Savage, and
T. Anderson, “Modeling
TCP latency,” in IEEE
INFOCOM,
[10] B. Sikdar, S. Kalyanaraman, and K. S. Vastola, “An integrated model for the latency and steady-state throughput of TCP connections,” Performance Evaluation, vol. 46, no. 2-3, pp. 139–154, 2001.
[11]
C. B. Samios and M. K. Vernon, “Modeling
the throughput of TCP Vegas,” in ACM SIGMETRICS,
[12] A. Misra and T. J. Ott, “The window distribution of multiple TCPs with random loss queues,” in IEEE GLOBECOM, 1999.
[13] V. Firoiu and M. Borden,
“A study of active queue management for congestion control,” in IEEE INFOCOM,
[14] T. Bu and D. Towsley, “Fixed
point approximations for TCP behavior in an AQM network,” in ACM SIGMETRICS,
[15] C. Casetti and M. Meo, “A new approach
to model the stationary behavior of TCP connections,” in IEEE INFOCOM,
[16] V. Misra, W. Gong, and D.
Towsley, “Stochastic
differential equation modeling and analysis of TCP-Windowsize behavior,” in
Proceeding of
PERFORMANCE,
[17] V. Misra, W.-B. Gong, and D. F. Towsley, “Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED,” in ACM SIGCOMM, 2000, pp. 151–160.
[18] E. Altman, K. Avrachenkov, and C. Barakat, “A stochastic model of TCP/IP with stationary random losses,” in ACM SIGCOMM, 2000.
[19] B. T. Eitan Altman, D.
Barman and M. Vojnovic, “Parallel TCP
sockets: Simple model, throughput and validation,” in IEEE INFOCOM,
[20] A. P. G. R. S. Ben Fred, T.
Bonald and J. W. Roberts, “Statistical
bandwidth sharing: a study of congestion at flow level,” in ACM SIGCOMM,
[21] R. K. J Beckers, I Hendrawan and R. van der Mei, “Generalized processor sharing performance models for internet access lines,” in 9th IFIP Conference on Performance Modelling and Evaluation of ATM and IP Networks, Budapest, 2001.
[22] D. M. Chiu and R. Jain, “Analysis of the increase and decrease algorithms for congestion avoidance in computer networks,” in Journal of Computer Networks and ISDN, vol. 17, 1989.
[23] C. V. Hollot, V. Misra, D. F. Towsley, and W. Gong, “A control theoretic analysis of RED,” in IEEE INFOCOM, 2001, pp. 1510–1519.
[24] A. Aggarwal, S. Savage, and
T. Anderson, “Understanding
the performance of TCP pacing,” in IEEE INFOCOM,
[25] Thomas Anderson, Andrew
Collins, Arvind Krishnamurthy, and John Zahorjan, “PCP:
Efficient Endpoint Congestion Control,” in NSDI,
[26]
S. Jaiswal, G. Iannaccone, C. Diot, J. Kurose, and D. Towsley, "Measurement and Classification of Out-of-Sequence
Packets in a Tier-1 IP backbone", in IEEE INFOCOM,
[27] S. Jaiswal, G. Iannaccone, C. Diot, J. Kurose, and D. Towsley, “Inferring TCP connection characteristics through passive measurements,” in IEEE INFOCOM, Hong Kong, 2004.
[28] S. Floyd, M. Handley, J.
Padhye, and J. Widmer, “Equation-based
congestion control for Unicast applications,”
[29]
T Bu, Y Liu, D Towsley, “On the
TCP-Friendliness of VoIP Traffic,” in IEEE INFOCOM,