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
针对大多数Q oS路由选择算法所存在的问题,采用多目标规划和业务区分的方法建立了满足多Q oS需求和网络资源利用率的路由选择数学模型,对F a llback+算法作了进一步扩充和改善.提出了一种新的F a llback++算法,它不仅能满足多Q oS约束,...针对大多数Q oS路由选择算法所存在的问题,采用多目标规划和业务区分的方法建立了满足多Q oS需求和网络资源利用率的路由选择数学模型,对F a llback+算法作了进一步扩充和改善.提出了一种新的F a llback++算法,它不仅能满足多Q oS约束,而且能高效地利用网络通信资源.分析得出该算法的时间复杂度和空间复杂度均为O(n*N2).仿真实验验证了该模型和算法的有效性和正确性.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.
文摘针对大多数Q oS路由选择算法所存在的问题,采用多目标规划和业务区分的方法建立了满足多Q oS需求和网络资源利用率的路由选择数学模型,对F a llback+算法作了进一步扩充和改善.提出了一种新的F a llback++算法,它不仅能满足多Q oS约束,而且能高效地利用网络通信资源.分析得出该算法的时间复杂度和空间复杂度均为O(n*N2).仿真实验验证了该模型和算法的有效性和正确性.
