Active queue versus passive queue — An experimental analysis on multi-hop wireless networks

R, Hema; Murugesan, G.; Jude, M. Joseph Auxilius; Diniesh, V. C.; SreeArthi, D.; Malini, S.

doi:10.1109/iccci.2017.8117774

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…For such scheduling, packets are dropped when the queue length exceeds the maximum length which results in the retransmission of a large number of packets in a short period of time. For such a network model, it is very difficult to control transmission throughput, delay and packet dropping [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Supervised Learning of Neural Networks for Active Queue Management in the Internet

Szyguła

Domański

Domańska

et al. 2021

Sensors

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The paper examines the AQM mechanism based on neural networks. The active queue management allows packets to be dropped from the router’s queue before the buffer is full. The aim of the work is to use machine learning to create a model that copies the behavior of the AQM PIα mechanism. We create training samples taking into account the self-similarity of network traffic. The model uses fractional Gaussian noise as a source. The quantitative analysis is based on simulation. During the tests, we analyzed the length of the queue, the number of rejected packets and waiting times in the queues. The proposed mechanism shows the usefulness of the Active Queue Management mechanism based on Neural Networks.

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Section: Introductionmentioning

confidence: 99%

Supervised Learning of Neural Networks for Active Queue Management in the Internet

Szyguła

Domański

Domańska

et al. 2021

Sensors

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“…In [67] the discrete-time queuing model of GRED algorithm was considered. The performance analysis of GRED (as well as other active queue and passive queue management algorithms) for multi-hop wireless relay networks was presented in [68]. The gentle parameter of GRED was reconsidered in [69].…”

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confidence: 99%

Chronology of the development of Active Queue Management algorithms of RED family. Part 1: from 1993 up to 2005

Zaryadov,

Viana,

Korolkova

et al. 2023

Discrete and Continuous Models

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Active queue versus passive queue — An experimental analysis on multi-hop wireless networks

Cited by 2 publications

References 16 publications

Supervised Learning of Neural Networks for Active Queue Management in the Internet

Supervised Learning of Neural Networks for Active Queue Management in the Internet

Chronology of the development of Active Queue Management algorithms of RED family. Part 1: from 1993 up to 2005

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