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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cet article, nous abordons le problème de la recherche de solutions réalisables au problème de routage de multidiffusion de groupe (GMRP). Ce problème est une généralisation du problème de routage multicast selon lequel chaque membre du groupe est autorisé à multidiffuser des messages vers d'autres membres du même groupe. Le problème de routage implique la construction d’un ensemble d’arbres de multidiffusion à faible coût avec des exigences de bande passante pour tous les membres du groupe du réseau. Nous prouvons d’abord que le problème de trouver des solutions réalisables au GMRP est NP-complet. Nous proposons ensuite un nouvel algorithme heuristique pour construire des solutions réalisables pour GMRP. Les résultats de simulation montrent que l’algorithme proposé est capable d’atteindre de bonnes performances en termes de capacité à trouver des solutions réalisables chaque fois qu’elles existent.
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Chor Ping LOW, Ning WANG, "On Finding Feasible Solutions for the Group Multicast Routing Problem" in IEICE TRANSACTIONS on Communications,
vol. E85-B, no. 1, pp. 268-277, January 2002, doi: .
Abstract: In this paper we addresses the problem of finding feasible solutions for the Group Multicast Routing Problem (GMRP). This problem is a generalization of the multicast routing problem whereby every member of the group is allowed to multicast messages to other members from the same group. The routing problem involves the construction of a set of low cost multicast trees with bandwidth requirements for all the group members in the network. We first prove that the problem of finding feasible solutions to GMRP is NP-complete. Following that we propose a new heuristic algorithm for constructing feasible solutions for GMRP. Simulation results show that our proposed algorithm is able to achieve good performance in terms of its ability of finding feasible solutions whenever one exist.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e85-b_1_268/_p
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@ARTICLE{e85-b_1_268,
author={Chor Ping LOW, Ning WANG, },
journal={IEICE TRANSACTIONS on Communications},
title={On Finding Feasible Solutions for the Group Multicast Routing Problem},
year={2002},
volume={E85-B},
number={1},
pages={268-277},
abstract={In this paper we addresses the problem of finding feasible solutions for the Group Multicast Routing Problem (GMRP). This problem is a generalization of the multicast routing problem whereby every member of the group is allowed to multicast messages to other members from the same group. The routing problem involves the construction of a set of low cost multicast trees with bandwidth requirements for all the group members in the network. We first prove that the problem of finding feasible solutions to GMRP is NP-complete. Following that we propose a new heuristic algorithm for constructing feasible solutions for GMRP. Simulation results show that our proposed algorithm is able to achieve good performance in terms of its ability of finding feasible solutions whenever one exist.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - On Finding Feasible Solutions for the Group Multicast Routing Problem
T2 - IEICE TRANSACTIONS on Communications
SP - 268
EP - 277
AU - Chor Ping LOW
AU - Ning WANG
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E85-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2002
AB - In this paper we addresses the problem of finding feasible solutions for the Group Multicast Routing Problem (GMRP). This problem is a generalization of the multicast routing problem whereby every member of the group is allowed to multicast messages to other members from the same group. The routing problem involves the construction of a set of low cost multicast trees with bandwidth requirements for all the group members in the network. We first prove that the problem of finding feasible solutions to GMRP is NP-complete. Following that we propose a new heuristic algorithm for constructing feasible solutions for GMRP. Simulation results show that our proposed algorithm is able to achieve good performance in terms of its ability of finding feasible solutions whenever one exist.
ER -