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Burst ratio for a versatile traffic model
We deal with a finite-buffer queue, in which arriving jobs are subject to loss due to buffer overflows. The burst ratio parameter, which reflects the tendency of losses to form long series, is studied in detail. Perhaps the most versatile model of the arrival stream is used, i.e. the batch Markovian...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342753/ https://www.ncbi.nlm.nih.gov/pubmed/35913903 http://dx.doi.org/10.1371/journal.pone.0272263 |
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author | Chydzinski, Andrzej |
author_facet | Chydzinski, Andrzej |
author_sort | Chydzinski, Andrzej |
collection | PubMed |
description | We deal with a finite-buffer queue, in which arriving jobs are subject to loss due to buffer overflows. The burst ratio parameter, which reflects the tendency of losses to form long series, is studied in detail. Perhaps the most versatile model of the arrival stream is used, i.e. the batch Markovian arrival process (BMAP). Among other things, it enables modeling the interarrival time density function, the interarrival time autocorrelation function and batch arrivals. The main contribution in an exact formula for the burst ratio in a queue with BMAP arrivals and arbitrary service time distribution. The formula is presented in an explicite, ready-to-use form. Additionally, the impact of various system parameters on the burst ratio is demonstrated in numerical examples. The primary application area of the results is computer networking, where the complex nature of traffic has a deep impact on the burst ratio. However, due to the versatile arrival model, the results can be applied in other fields as well. |
format | Online Article Text |
id | pubmed-9342753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93427532022-08-02 Burst ratio for a versatile traffic model Chydzinski, Andrzej PLoS One Research Article We deal with a finite-buffer queue, in which arriving jobs are subject to loss due to buffer overflows. The burst ratio parameter, which reflects the tendency of losses to form long series, is studied in detail. Perhaps the most versatile model of the arrival stream is used, i.e. the batch Markovian arrival process (BMAP). Among other things, it enables modeling the interarrival time density function, the interarrival time autocorrelation function and batch arrivals. The main contribution in an exact formula for the burst ratio in a queue with BMAP arrivals and arbitrary service time distribution. The formula is presented in an explicite, ready-to-use form. Additionally, the impact of various system parameters on the burst ratio is demonstrated in numerical examples. The primary application area of the results is computer networking, where the complex nature of traffic has a deep impact on the burst ratio. However, due to the versatile arrival model, the results can be applied in other fields as well. Public Library of Science 2022-08-01 /pmc/articles/PMC9342753/ /pubmed/35913903 http://dx.doi.org/10.1371/journal.pone.0272263 Text en © 2022 Andrzej Chydzinski https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Chydzinski, Andrzej Burst ratio for a versatile traffic model |
title | Burst ratio for a versatile traffic model |
title_full | Burst ratio for a versatile traffic model |
title_fullStr | Burst ratio for a versatile traffic model |
title_full_unstemmed | Burst ratio for a versatile traffic model |
title_short | Burst ratio for a versatile traffic model |
title_sort | burst ratio for a versatile traffic model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342753/ https://www.ncbi.nlm.nih.gov/pubmed/35913903 http://dx.doi.org/10.1371/journal.pone.0272263 |
work_keys_str_mv | AT chydzinskiandrzej burstratioforaversatiletrafficmodel |