Cargando…

Impact of the Dropping Function on Clustering of Packet Losses

The dropping function mechanism is known to improve the performance of TCP/IP networks by reducing queueing delays and desynchronizing flows. In this paper, we study yet another positive effect caused by this mechanism, i.e., the reduction in the clustering of packet losses, measured by the burst ra...

Descripción completa

Detalles Bibliográficos
Autor principal: Chydzinski, Andrzej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609635/
https://www.ncbi.nlm.nih.gov/pubmed/36298229
http://dx.doi.org/10.3390/s22207878
_version_ 1784819070404657152
author Chydzinski, Andrzej
author_facet Chydzinski, Andrzej
author_sort Chydzinski, Andrzej
collection PubMed
description The dropping function mechanism is known to improve the performance of TCP/IP networks by reducing queueing delays and desynchronizing flows. In this paper, we study yet another positive effect caused by this mechanism, i.e., the reduction in the clustering of packet losses, measured by the burst ratio. The main contribution consists of two new formulas for the burst ratio in systems with and without the dropping function, respectively. These formulas enable the easy calculation of the burst ratio for a general, non-Poisson traffic, and for an arbitrary form of the dropping function. Having the formulas, we provide several numerical examples that demonstrate their usability. In particular, we test the effect of the dropping function’s shape on the burst ratio. Several shapes of the dropping function proposed in the literature are compared in this context. We also demonstrate, how the optimal shape can be found in a parameter-depended class of functions. Finally, we investigate the impact of different system parameters on the burst ratio, including the load of the system and the variance of the service time. The most important conclusion drawn from these examples is that it is not only the dropping function that reduces the burst ratio by far; simultaneously, the more variable the traffic, the more beneficial the application of the dropping function.
format Online
Article
Text
id pubmed-9609635
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-96096352022-10-28 Impact of the Dropping Function on Clustering of Packet Losses Chydzinski, Andrzej Sensors (Basel) Article The dropping function mechanism is known to improve the performance of TCP/IP networks by reducing queueing delays and desynchronizing flows. In this paper, we study yet another positive effect caused by this mechanism, i.e., the reduction in the clustering of packet losses, measured by the burst ratio. The main contribution consists of two new formulas for the burst ratio in systems with and without the dropping function, respectively. These formulas enable the easy calculation of the burst ratio for a general, non-Poisson traffic, and for an arbitrary form of the dropping function. Having the formulas, we provide several numerical examples that demonstrate their usability. In particular, we test the effect of the dropping function’s shape on the burst ratio. Several shapes of the dropping function proposed in the literature are compared in this context. We also demonstrate, how the optimal shape can be found in a parameter-depended class of functions. Finally, we investigate the impact of different system parameters on the burst ratio, including the load of the system and the variance of the service time. The most important conclusion drawn from these examples is that it is not only the dropping function that reduces the burst ratio by far; simultaneously, the more variable the traffic, the more beneficial the application of the dropping function. MDPI 2022-10-17 /pmc/articles/PMC9609635/ /pubmed/36298229 http://dx.doi.org/10.3390/s22207878 Text en © 2022 by the author. 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
Impact of the Dropping Function on Clustering of Packet Losses
title Impact of the Dropping Function on Clustering of Packet Losses
title_full Impact of the Dropping Function on Clustering of Packet Losses
title_fullStr Impact of the Dropping Function on Clustering of Packet Losses
title_full_unstemmed Impact of the Dropping Function on Clustering of Packet Losses
title_short Impact of the Dropping Function on Clustering of Packet Losses
title_sort impact of the dropping function on clustering of packet losses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609635/
https://www.ncbi.nlm.nih.gov/pubmed/36298229
http://dx.doi.org/10.3390/s22207878
work_keys_str_mv AT chydzinskiandrzej impactofthedroppingfunctiononclusteringofpacketlosses