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Minimum cost multiple multicast network coding with quantized rates
Authors:MA Raayatpanah  H Salehi Fathabadi  BH Khalaj  S Khodayifar
Affiliation:1. School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran;2. Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;1. ICTEAM, Université catholique de Louvain, Louvain-la-Neuve, Belgium;2. LSIIT, Université de Strasbourg, Strasbourg, France;1. Department of Electrical Engineering, KAIST, Daejeon, South Korea;2. Communication Lab., LIG Nex1, Seongnam-City, Gyeonggi-do, South Korea;1. Vienna University of Technology, Institute of Telecommunications, Favoritenstrasse 9-11/389, 1040 Vienna, Austria;2. Department of Information Technology (INTEC) of Ghent University – iMinds, Gaston Crommenlaan 8, B-9050 Gent, Belgium;1. Université de Bretagne-Sud, UMR 6285, Lab-STICC, CNRS, Centre de recherche, Lorient, France;2. Universidad de los Andes, Departamento de Ingeniería Industrial, Bogotá, Colombia;1. NETLAB, Department of Computer Engineering, Bogazici University, Istanbul, TR-34342, Turkey;2. Department of Mathematics, Bogazici University, Istanbul, TR-34342, Turkey
Abstract:In this paper, we consider multiple multicast sessions with intra-session network coding where rates over all links are integer multiples of a basic rate. Although having quantized rates over communication links is quite common, conventional minimum cost network coding problem cannot generally result in quantized solutions. In this research, the problem of finding minimum cost transmission for multiple multicast sessions with network coding is addressed. It is assumed that the rate of coded packet injection at every link of each session takes quantized values. First, this problem is formulated as a mixed integer linear programming problem, and then it is proved that this problem is strongly NP-hard on general graphs. In order to obtain an exact solution for the problem, an effective and efficient scheme based on Benders decomposition is developed. Using this scheme the problem is decomposed into a master integer programming problem and several linear programming sub-problems. The efficiency of the proposed scheme is subsequently evaluated by numerical results on random networks.
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