A Simple Solution to Find the Distribution of TCP Window Sizes

Yan, Jinyao; Plattner, Bernhard

doi:10.1109/lcomm.2013.010313.122085

Cited by 5 publications

(25 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equation evaluates f ( p ), which is the expression in terms of p . Yan and Plattner have determined the distribution of TCP window sizes. They have modeled for two cases, viz, one when loss indication is due to TD and second, if loss indication is due to both TD and TO.…”

Section: Related Workmentioning

confidence: 99%

“…There exists a latest model seen by us that describes the probability density function and cumulative distribution function (CDF). We observe one issue with a model developed by Yan and Plattner after examining on ns‐2. A limitation on the congestion window size becomes a very important concern when the receiver has limited buffer size.…”

Section: Introductionmentioning

confidence: 95%

“…The TCP protocol enables a mechanism to control the sending rate that leads to reduction in overflow at the receiver. The variety of TCP models are available in the literature …”

Section: Introductionmentioning

confidence: 99%

“…The window size can grow up to W max without loss, but if it grows further, then loss will be observed. The existing model does not work for such a situation when buffer size is limited to some fixed value. To make the completeness of the model, we have been motivated to propose a new model that works for this situation that contributes to fill the gap of research.…”

Section: Introductionmentioning

confidence: 99%

“…The performance evaluation for distribution of congestion window size and TDP has been presented in Section . We have evaluated our analytical model with simulated data, which is performed on ns‐2 and also compared with Yan et al model. In the last section, we conclude the paper.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Comparative analysis of cumulative distribution function for TCP congestion window size and triple‐duplicate period

Patel

2019

Int J Communication

View full text Add to dashboard Cite

Summary Various version of Transmission Control Protocol (TCP) congestion window model are available in the literature. TCP congestion control is handled in two phases: (a) slow start and (b) congestion avoidance. This paper deals with congestion avoidance phase that is based on additive increase multiplicative decrease (AIMD) mechanism in which window size either increase by one or cuts to half of the previous window size. For distribution of window sizes, a model developed by Yan et al has been presented for two loss indications: (a) triple duplicate (TD) and (b) time‐outs (TOs) only while it does not deal with the window size limitation. It does not allow to cap over the TCP congestion window size if the buffer size is restricted to a fixed value though window size could not move beyond that. The unconstrained window size moves on in the presence of low loss probability. In this paper, we propose a model for the case where the window size is bounded by a maximum value that makes applicable to window size limitation as well. Further, the work has been extended to develop a new model that obtains a cumulative distribution function for TD periods (TDPs). The proposed model is validated on ns‐2, and we conclude that observed results for distribution function are very closed to our proposed model.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

“…The TCP protocol enables a mechanism to control the sending rate that leads to reduction in overflow at the receiver. The variety of TCP models are available in the literature …”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparative analysis of cumulative distribution function for TCP congestion window size and triple‐duplicate period

Patel

2019

Int J Communication

View full text Add to dashboard Cite

show abstract

A stochastic approximation approach to active queue management

2017

View full text Add to dashboard Cite

Recently, a dynamic adaptive queue management with random dropping (AQMRD) scheme has been developed to capture the time-dependent variation of average queue size by incorporating the rate of change of average queue size as a parameter. A major issue with AQMRD is the choice of parameters. In this paper, a novel online stochastic approximation based optimization scheme is proposed to dynamically tune the parameters of AQMRD and which is also applicable for other active queue management (AQM) algorithms. Our optimization scheme significantly improves the throughput, average queue size, and loss-rate in relation to other AQM schemes.

show abstract

Accurate mathematical modeling and solution of TCP congestion window size distribution

Luan

Beaulieu

2020

Computer Communications

View full text Add to dashboard Cite

A Simple Solution to Find the Distribution of TCP Window Sizes

Cited by 5 publications

References 9 publications

Comparative analysis of cumulative distribution function for TCP congestion window size and triple‐duplicate period

Comparative analysis of cumulative distribution function for TCP congestion window size and triple‐duplicate period

A stochastic approximation approach to active queue management

Accurate mathematical modeling and solution of TCP congestion window size distribution

Contact Info

Product

Resources

About