Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Analysis of the increase and decrease algorithms for congestion avoidance in computer networks
Computer Networks and ISDN Systems
Observations on the dynamics of a congestion control algorithm: the effects of two-way traffic
SIGCOMM '91 Proceedings of the conference on Communications architecture & protocols
Detection of pathological TCP connections using a segment trace filter
ACM SIGCOMM Computer Communication Review
Observing TCP dynamics in real networks
SIGCOMM '92 Conference proceedings on Communications architectures & protocols
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
TCP/IP illustrated (vol. 2): the implementation
TCP/IP illustrated (vol. 2): the implementation
Simulation-based comparisons of Tahoe, Reno and SACK TCP
ACM SIGCOMM Computer Communication Review
Automated packet trace analysis of TCP implementations
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
The macroscopic behavior of the TCP congestion avoidance algorithm
ACM SIGCOMM Computer Communication Review
End-to-end internet packet dynamics
IEEE/ACM Transactions on Networking (TON)
Modeling TCP Reno performance: a simple model and its empirical validation
IEEE/ACM Transactions on Networking (TON)
Equation-based congestion control for unicast applications
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Critical path analysis of TCP transactions
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
A stochastic model of TCP/IP with stationary random losses
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
FLID-DL: congestion control for layered multicast
COMM '00 Proceedings of NGC 2000 on Networked group communication
A Stochastic Model of TCP Reno Congestion Avoidence and Control
A Stochastic Model of TCP Reno Congestion Avoidence and Control
Control mechanisms for packet audio in the internet
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 1
Throughput analysis of TCP on channels with memory
IEEE Journal on Selected Areas in Communications
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
Dynamic buffer management scheme based on rate estimation in packet-switched networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analytical computation of completion time distributions of short-lived TCP connections
Performance Evaluation - Performance modelling and evaluation of heterogeneous networks
Analytical computation of completion time distributions of short-lived TCP connections
Performance Evaluation
Performance analysis and improvement of PR-SCTP for small messages
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Recently, several researchers have developed equations for modeling TCP behaviors, such as the expected throughput or latency, based on Markov chains derived from TCP with additional simplifying assumptions. In this paper, we suggest new directions for Markov chain analyses of TCP. Our first contribution is to closely examine not just the expectation but the entire cumulative distribution function of transfer times under various models. Particularly for short or medium transfers, the distribution is likely to be more useful than the expectation in terms of measuring end-user satisfaction. We find that the shapes of TCP cumulative distribution functions are remarkably robust to small changes in the model. Our results suggest that simplifying Markov analyses can be extended to yield approximations for the entire distribution as well as for the expectation.Our second contribution is to consider correction procedures to enhance these models. A correction procedure is a rule of thumb that allows equations from one model to be used in other situations. As an example, several analyses use a Drop-Tail loss model. We determine correction procedures for the deviation between this model and other natural loss models based on simulations. The existence of a simple correction procedure in this instance suggests that the high-level behavior of TCP is robust against changes in the loss model.