Traffic distribution for end-to-end QoS routing with multicast multichannel services
With the development of multimedia group applications and multicasting demands, the construction of multicast routing tree satisfying Quality of Service (QoS) is more important. A multicast tree, which is constructed by existing multicast algorithms, suffers three major weaknesses: (1) it cannot be constructed by multichannel routing, transmitting a message using all available links, thus the data traffic cannot be preferably distributed; (2) it does not formulate duplication capacity; consequently, duplication capacity in each node cannot be optimally distributed; (3) it cannot change the number of links and nodes used optimally. In fact, it cannot employ and cover unused backup multichannel paths optimally. To overcome these weaknesses, this paper presents a polynomial time algorithm for distributed optimal multicast routing and Quality of Service (QoS) guarantees in networks with multichannel paths which is called Distributed Optimal Multicast Multichannel Routing Algorithm (DOMMR). The aim of this algorithm is: (1) to minimize End-to-End delay across the multichannel paths, (2) to minimize consumption of bandwidth by using all available links, and (3) to maximize data rate by formulating network resources. DOMMR is based on the Linear Programming Formulation (LPF) and presents an iterative optimal solution to obtain the best distributed routes for traffic demands between all edge nodes. Computational experiments and numerical simulation results will show that the proposed algorithm is more efficient than the existing methods. The simulation results are obtained by applying network simulation tools such as QSB, OpNet and MATLB to some samples of network. We then introduce a generalized problem, called the delay-constrained multicast multichannel routing problem, and show that this generalized problem can be solved in polynomial time.
KeywordsMulticasting Multichannel path Optimized routing Quality of services Traffic Distribution Linear programming
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