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Performance modeling, loss networks, and statistical multiplexing
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology...
Autor principal: | |
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Lenguaje: | eng |
Publicado: |
Morgan & Claypool Publ.
2009
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2104645 |
_version_ | 1780948789299773440 |
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author | Mazumdar, Ravi |
author_facet | Mazumdar, Ravi |
author_sort | Mazumdar, Ravi |
collection | CERN |
description | This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I |
id | cern-2104645 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2009 |
publisher | Morgan & Claypool Publ. |
record_format | invenio |
spelling | cern-21046452021-04-21T20:02:34Zhttp://cds.cern.ch/record/2104645engMazumdar, RaviPerformance modeling, loss networks, and statistical multiplexingEngineeringThis monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. IMorgan & Claypool Publ.oai:cds.cern.ch:21046452009 |
spellingShingle | Engineering Mazumdar, Ravi Performance modeling, loss networks, and statistical multiplexing |
title | Performance modeling, loss networks, and statistical multiplexing |
title_full | Performance modeling, loss networks, and statistical multiplexing |
title_fullStr | Performance modeling, loss networks, and statistical multiplexing |
title_full_unstemmed | Performance modeling, loss networks, and statistical multiplexing |
title_short | Performance modeling, loss networks, and statistical multiplexing |
title_sort | performance modeling, loss networks, and statistical multiplexing |
topic | Engineering |
url | http://cds.cern.ch/record/2104645 |
work_keys_str_mv | AT mazumdarravi performancemodelinglossnetworksandstatisticalmultiplexing |