Multicasting Algorithms in Multimedia Networks

• Main Authors: Hsu-Chen Cheng, 鄭旭成
• Other Authors: 林永松
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/51373998482958752539

博士 === 國立臺灣大學 === 資訊管理學研究所 === 93 === Based on recent developments in transmission and computing technologies, multimedia applications, such as the teleconferencing and video on demand, have already become achievable and are comprehensively and widely used. Nevertheless, most of these applications require a large amount of bandwidth to deliver multimedia information to multiple destinations simultaneously. One possible way to meet this requirement is via multicasting. Multimedia application environments are characterized by large bandwidth variations due to the heterogeneous access technologies of networks (e.g. analog modem, cable modem, xDSL, and wireless access etc.) and different receivers’ quality requirements. In video multicasting, the heterogeneity of the networks and destinations makes it difficult to achieve bandwidth efficiency and service flexibility. There are many challenging issues that need to be addressed in designing architectures and mechanisms for multicast data transmission. Taking advantage of recent advances in video encoding and transmission technologies, either by a progress coder or video gateway, different destinations can request a different bandwidth requirement from the source. The source then only needs to transmit signals that are sufficient for the highest bandwidth destination into a single multicast tree. In this dissertation, we study several multicast routing problems, which belong to both single-rate and multi-rate categories. Mathematical formulations are used to model the planning and operational problems, and Lagrangean relaxation techniques, based on the proposed mathematical formulations, are adopted to solve the network planning and operational problems. The scope and contributions of this dissertation are highlighted by the following. For the min-cost multirate multicasting routing problem, we propose some heuristics to jointly determine the following decision variables: (1) the routing assignment; and (2) the maximum allowable traffic rate of each multicast user group through each link. We successfully model the traffic flow on the links for multi-rate multicasting, and the proposed optimization-based heuristic outperform than the heuristic proposed in the earlier researches. We also deal with the multi-group multicasting planning problem with a capacity constraint. We also consider the call admission control issues for the single-rate and multi-rate multicasting. We consider the problem of maximum-revenue routing with a partial admission control mechanism. The mechanism means that the admission policy of a multicast group is not based on a traditional “all or none” strategy. Instead it considers accepting partial destinations for the requested multicast group. For a given network topology, a given link capacity, destinations of a multicast group, and the bandwidth requirement of each destination, we attempt to find a feasible routing solution to execute call admission control and apply resource reservation to maximize the revenue of the multicast trees. In addition, we propose a real-time model to deal with long term revenue analysis. The improvement is up to 186% better than the simple algorithm in single-rate transmission, and 905% in multi-rate transmission. Furthermore, we address the problem of constructing a minimum cost multicast tree by considering dynamic user membership. The motivation of this is to create a mechanism for finding and evaluating the cost-efficiency of a multicast tree with a given network and a fixed set of group members. Unlike other minimum cost multicast tree algorithms, this problem consists of one multicast group of fixed members, where each destination member is dynamic and has a probability of being active, which is observed over some period of time. The improvement of our proposed algorithm is up to 38%. Finally, we point out five challenging issues to be tackled in the future. We also proposed some feasible mathematical models to formulate these problems. These models are based on the research results of the dissertation.