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Article

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Title

Traffic engineering for multicast connections in multiservice cellular networks

Authors

[ 1 ] Katedra Sieci Telekomunikacyjnych i Komputerowych, Wydział Elektroniki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Year of publication

2013

Published in

IEEE Transactions on Industrial Informatics

Journal year: 2013 | Journal volume: vol. 9 | Journal number: no. 1

Article type

scientific article

Publication language

english

Keywords
EN
  • cellular networks
  • modeling
  • multicast
Abstract

EN The dynamic development of multiservice cellular networks has resulted in significant changes in the system architecture, which, in turn, has led to a broad distribution of many mechanisms and functions responsible for traffic management. These mechanisms take advantage of appropriate algorithms and analytic dependencies to ensure optimal quality of service that can be tailored to the objectives of the network operator. This paper proposes a new analytical model of a cellular network that supports multicast connections in a distributed environment. It is assumed that, in the cells participating in multicast connections, it is possible to apply different and independent traffic management mechanisms such as, for example, threshold mechanisms and resource reservation mechanisms. The proposed method can be used in an evaluation and scientific methods of research in the traffic effectiveness of multicast connections in given load conditions of a cellular network. An application of the method can have a particular significance in designing high-bit-rate multicast services to users in 4G networks. The analytical model proposed in this paper is verified on the basis of simulation examinations of cellular networks with multicast connections. The investigations confirm high accuracy of the model and the correctness of all theoretical assumptions adopted in the study.

Pages (from - to)

262 - 270

DOI

10.1109/TII.2012.2188902

URL

https://ieeexplore.ieee.org/document/6158601

Ministry points / journal

50

Impact Factor

8,785

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