[ Approche stochastique de la congestion dans les réseaux 2G à 4G+ ]
Volume 26, Issue 4, July 2019, Pages 1004–1021
BADIBI OMAK A. Christopher1 and Kalala Mutombo Franck2
1 Département de Mathématique, Faculté des Sciences, Université de Lubumbashi, BP 1825, Lubumbashi, RD Congo
2 Departement de Mathématique, Faculté des Sciences, Université de Lubumbashi, BP 1825, Lubumbashi, RD Congo
Original language: French
Copyright © 2019 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents the stochastic approach to congestion that is unknown to some users or designers of telecommunication networks. Its purpose is to help designers predict network behavior, characterize load, determine number and size of components, these elements are important for those who want to optimize the network in terms of its architecture, so as to meet the required quality of service standards by taking the most economical route possible. This approach will be based on the modelizations of the arrival and the waiting calls on the network following some hypotheses. A key element of call reception to consider is the base transmission station (BTS) in the GSM network or the NODE B in the 3G to 4G + networks.
Author Keywords: Telecommunications Networks, Stochastic Processes, Markov Chains and Queuing Networks.
Volume 26, Issue 4, July 2019, Pages 1004–1021
BADIBI OMAK A. Christopher1 and Kalala Mutombo Franck2
1 Département de Mathématique, Faculté des Sciences, Université de Lubumbashi, BP 1825, Lubumbashi, RD Congo
2 Departement de Mathématique, Faculté des Sciences, Université de Lubumbashi, BP 1825, Lubumbashi, RD Congo
Original language: French
Copyright © 2019 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper presents the stochastic approach to congestion that is unknown to some users or designers of telecommunication networks. Its purpose is to help designers predict network behavior, characterize load, determine number and size of components, these elements are important for those who want to optimize the network in terms of its architecture, so as to meet the required quality of service standards by taking the most economical route possible. This approach will be based on the modelizations of the arrival and the waiting calls on the network following some hypotheses. A key element of call reception to consider is the base transmission station (BTS) in the GSM network or the NODE B in the 3G to 4G + networks.
Author Keywords: Telecommunications Networks, Stochastic Processes, Markov Chains and Queuing Networks.
Abstract: (french)
Cet article présente l'approche stochastique de la congestion plutôt méconnus pour certains utilisateurs ou concepteurs des réseaux de télécommunications. Elle a pour but d'aider les concepteurs à prédire le comportement du réseau, caractériser la charge, déterminer le nombre et la taille des composantes nécessaires pour enfin prédire la performance du réseau sous des charges futures. Ces éléments sont importants pour ceux qui veulent optimiser le réseau au niveau de son architecture, de manière à satisfaire les standards de qualité de service requis en empruntant la voie la plus économique possible. Cette approche se base sur les modélisations de l'arrivée, de la mise en attente et du blocage des appels sur le réseau suivant certaines hypothèses. Un élément capital de réception d'appel à considérer est la station de transmission de base (BTS) dans le réseau GSM ou la NODE B dans les réseaux 3G à 4G+.
Author Keywords: Réseaux de télécommunications, Processus stochastiques, chaines de Markov et Réseaux des Files d'attentes.
How to Cite this Article
BADIBI OMAK A. Christopher and Kalala Mutombo Franck, “Stochastic approach of congestion in 2G to 4G+ networks,” International Journal of Innovation and Applied Studies, vol. 26, no. 4, pp. 1004–1021, July 2019.
