The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMR...The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMRGA, a multicast routing policy for Internet, mobile network or other highperformance networks is mainly presented, which is based on the genetic algorithm(GA), and can provide QoSsensitive paths in a scalable and flexible way in the network environment with uncertain parameters. The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or nearoptimal solution within few iterations, even for the network environment with uncertain parameters. The incremental rate of computational cost can be close to a polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated by using simulations. The results show that QMRGA provides an available approach to QoS multicast routing in network environment with uncertain parameters.展开更多
Constraint-based multicast routing, which aims at identifying a path that satisfies a set of quality of service (QoS) constraints, has became a very important research issue in the areas of networks and distributed sy...Constraint-based multicast routing, which aims at identifying a path that satisfies a set of quality of service (QoS) constraints, has became a very important research issue in the areas of networks and distributed systems. In general, multi-constrained path selection with or without optimization is a NP-complete problem that can not be exactly solved in polynomial time. Hence, accurate constraints-based routing algorithms with a fast running time are scarce, perhaps even non-existent. The expected impact of such a constrained-based routing algorithm has resulted in the proposal of numerous heuristics and a few exact QoS algorithms. This paper aims to give a thorough, concise and fair evaluation of the most important multiple constraint-based QoS multicast routing algorithms known today, and it provides a descriptive overview and simulation results of these multi-constrained routing algorithms.展开更多
Most of the multimedia applications require strict Quality-of-Service (QoS) guarantee during the communication between a single source and multiple destinations. The paper mainly presents a QoS Multicast Routing algor...Most of the multimedia applications require strict Quality-of-Service (QoS) guarantee during the communication between a single source and multiple destinations. The paper mainly presents a QoS Multicast Routing algorithms based on Genetic Algorithm (QMRGA). Simulation results demonstrate that the algorithm is capable of discovering a set of QoS-based near optimized, non-dominated multicast routes within a few iterations, even for the networks environment with uncertain parameters.展开更多
为了提高网络路由性能,提出并设计了一种基于遗传-蚁群优化算法的服务质量(quality of service,QoS)组播路由算法。首先,设计了自适应变频采集策略用于采集网络与节点信息,以此获得网络和节点的状态,为后续路由优化提供数据支持;其次,...为了提高网络路由性能,提出并设计了一种基于遗传-蚁群优化算法的服务质量(quality of service,QoS)组播路由算法。首先,设计了自适应变频采集策略用于采集网络与节点信息,以此获得网络和节点的状态,为后续路由优化提供数据支持;其次,计算路径代价,将路径代价最小作为优化目标,建立QoS组播路由优化模型,并设置相关约束条件;最后,结合遗传算法和蚁群算法提出一种遗传-蚁群优化算法求解上述模型,输出最优路径,完成路由优化。实验结果表明,所提算法可有效降低路径长度与路径代价,提高搜索效率与路由请求成功率,优化后的路由时延抖动较小。展开更多
In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicas...In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.展开更多
文摘The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMRGA, a multicast routing policy for Internet, mobile network or other highperformance networks is mainly presented, which is based on the genetic algorithm(GA), and can provide QoSsensitive paths in a scalable and flexible way in the network environment with uncertain parameters. The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or nearoptimal solution within few iterations, even for the network environment with uncertain parameters. The incremental rate of computational cost can be close to a polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated by using simulations. The results show that QMRGA provides an available approach to QoS multicast routing in network environment with uncertain parameters.
文摘Constraint-based multicast routing, which aims at identifying a path that satisfies a set of quality of service (QoS) constraints, has became a very important research issue in the areas of networks and distributed systems. In general, multi-constrained path selection with or without optimization is a NP-complete problem that can not be exactly solved in polynomial time. Hence, accurate constraints-based routing algorithms with a fast running time are scarce, perhaps even non-existent. The expected impact of such a constrained-based routing algorithm has resulted in the proposal of numerous heuristics and a few exact QoS algorithms. This paper aims to give a thorough, concise and fair evaluation of the most important multiple constraint-based QoS multicast routing algorithms known today, and it provides a descriptive overview and simulation results of these multi-constrained routing algorithms.
基金Supported by the National Natural Science Foundation of China (No.90304018)Natural Science Foundation of Hubei Province (No.2004ABA014)Teaching Research Project of Higher Educational Institutions of Hubei Province (No.20040231).
文摘Most of the multimedia applications require strict Quality-of-Service (QoS) guarantee during the communication between a single source and multiple destinations. The paper mainly presents a QoS Multicast Routing algorithms based on Genetic Algorithm (QMRGA). Simulation results demonstrate that the algorithm is capable of discovering a set of QoS-based near optimized, non-dominated multicast routes within a few iterations, even for the networks environment with uncertain parameters.
基金Acknowledgements： This work is supported by National Natural Science Foundation of China （No. 60172035, 90304018）, NSF of Hubei Province （No. 2004ABA014）, and Teaching Research Project of Higher Educational Institutions of Hubei Province （No. 20040231）.
文摘为了提高网络路由性能,提出并设计了一种基于遗传-蚁群优化算法的服务质量(quality of service,QoS)组播路由算法。首先,设计了自适应变频采集策略用于采集网络与节点信息,以此获得网络和节点的状态,为后续路由优化提供数据支持;其次,计算路径代价,将路径代价最小作为优化目标,建立QoS组播路由优化模型,并设置相关约束条件;最后,结合遗传算法和蚁群算法提出一种遗传-蚁群优化算法求解上述模型,输出最优路径,完成路由优化。实验结果表明,所提算法可有效降低路径长度与路径代价,提高搜索效率与路由请求成功率,优化后的路由时延抖动较小。
文摘In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.
