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On the Influence of AQM on Serialization of Packet Losses

We study the influence of the active queue management mechanism based on the queue size on the serialization of packet losses, i.e., the occurrences of losses in long, consecutive series. We use a traffic model able to mimic precisely the autocorrelation function of traffic, which is known to be far...

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Detalles Bibliográficos
Autores principales: Chydzinski, Andrzej, Adamczyk, Blazej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961450/
https://www.ncbi.nlm.nih.gov/pubmed/36850800
http://dx.doi.org/10.3390/s23042197
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author Chydzinski, Andrzej
Adamczyk, Blazej
author_facet Chydzinski, Andrzej
Adamczyk, Blazej
author_sort Chydzinski, Andrzej
collection PubMed
description We study the influence of the active queue management mechanism based on the queue size on the serialization of packet losses, i.e., the occurrences of losses in long, consecutive series. We use a traffic model able to mimic precisely the autocorrelation function of traffic, which is known to be far from zero in packet networks. The main contribution is a theorem on the burst ratio parameter, describing the serialization of losses, proven for an arbitrary function assigning drop probabilities to queue sizes. In numerical examples, we show the impact of the autocorrelation strength, drop probability function, and load of the link, on the serialization of losses.
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spelling pubmed-99614502023-02-26 On the Influence of AQM on Serialization of Packet Losses Chydzinski, Andrzej Adamczyk, Blazej Sensors (Basel) Article We study the influence of the active queue management mechanism based on the queue size on the serialization of packet losses, i.e., the occurrences of losses in long, consecutive series. We use a traffic model able to mimic precisely the autocorrelation function of traffic, which is known to be far from zero in packet networks. The main contribution is a theorem on the burst ratio parameter, describing the serialization of losses, proven for an arbitrary function assigning drop probabilities to queue sizes. In numerical examples, we show the impact of the autocorrelation strength, drop probability function, and load of the link, on the serialization of losses. MDPI 2023-02-15 /pmc/articles/PMC9961450/ /pubmed/36850800 http://dx.doi.org/10.3390/s23042197 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chydzinski, Andrzej
Adamczyk, Blazej
On the Influence of AQM on Serialization of Packet Losses
title On the Influence of AQM on Serialization of Packet Losses
title_full On the Influence of AQM on Serialization of Packet Losses
title_fullStr On the Influence of AQM on Serialization of Packet Losses
title_full_unstemmed On the Influence of AQM on Serialization of Packet Losses
title_short On the Influence of AQM on Serialization of Packet Losses
title_sort on the influence of aqm on serialization of packet losses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961450/
https://www.ncbi.nlm.nih.gov/pubmed/36850800
http://dx.doi.org/10.3390/s23042197
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