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
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
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
An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although ...An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although the proposed algorithm has exponential time complexity in the worst case, it can get the running results quickly in practical application. When the scale of network increases, the algorithm can efficiently control the size of search space by constraint conditions and prior queue. The results of simulation show that successful request ratio ( r ) of efficient algorithm for multi-constrained optimal path (EAMCOP) is better than that of heuristic algorithm for multi-constrained optimal path (H-MCOP), but average computing time ( t ) of EAMCOP is far less than that of H-MCOP. And it can be seen that the computing time of EAMCOP is only one fourth of that of H-MCOP in Advanced Research Projects Agency Network (ARPANet) topology.展开更多
To improve the Quality of Service (QoS)-aware Web service compositions considering constraints between cross-organizational business,this paper analyzes the types of constraints,and accordingly proposes a Chaos Geneti...To improve the Quality of Service (QoS)-aware Web service compositions considering constraints between cross-organizational business,this paper analyzes the types of constraints,and accordingly proposes a Chaos Genetic Algorithm (CGA). The algorithm creates an initial population of service compositions based on the chaos theory,and then processes individuals which violate constraints in the initial population using repair strategies. Next,a new fitness function is designed to gradually eliminate the infeasible compositions generated in evolution. Finally,the algorithm makes minor chaotic disturbances on the evolved group to accelerate convergence and avoid local optimum. Experimental results demonstrate the effectiveness of the proposed algorithm.展开更多
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.
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An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although the proposed algorithm has exponential time complexity in the worst case, it can get the running results quickly in practical application. When the scale of network increases, the algorithm can efficiently control the size of search space by constraint conditions and prior queue. The results of simulation show that successful request ratio ( r ) of efficient algorithm for multi-constrained optimal path (EAMCOP) is better than that of heuristic algorithm for multi-constrained optimal path (H-MCOP), but average computing time ( t ) of EAMCOP is far less than that of H-MCOP. And it can be seen that the computing time of EAMCOP is only one fourth of that of H-MCOP in Advanced Research Projects Agency Network (ARPANet) topology.
基金National Natural Science Fund of China(61672022,61272036)Graduate Innovation Program of Shanghai Polytechnic University(A01GY17F022)Key Discipline of Shanghai Polytechnic University(XXKZD1604)
文摘To improve the Quality of Service (QoS)-aware Web service compositions considering constraints between cross-organizational business,this paper analyzes the types of constraints,and accordingly proposes a Chaos Genetic Algorithm (CGA). The algorithm creates an initial population of service compositions based on the chaos theory,and then processes individuals which violate constraints in the initial population using repair strategies. Next,a new fitness function is designed to gradually eliminate the infeasible compositions generated in evolution. Finally,the algorithm makes minor chaotic disturbances on the evolved group to accelerate convergence and avoid local optimum. Experimental results demonstrate the effectiveness of the proposed algorithm.
