Dynamic multicast traffic grooming in wave-length division multiplexing(WDM)networks was analyzed to minimize networkwide costs and to increase the network resource utilization.A network model was developed for dynami...Dynamic multicast traffic grooming in wave-length division multiplexing(WDM)networks was analyzed to minimize networkwide costs and to increase the network resource utilization.A network model was developed for dynamic multicast traffic grooming with resource constraints and an algorithm that can provide quality of service(QoS)was proposed.The QoS is measured by the maximum number of lightpaths passing between the source and the destinations.The blocking probability of the algorithm was assessed in simulations.The results show that a higher QoS requirement results in higher blocking probability,and when the QoS requirement is low,changes in the QoS require-ments have only small effects on the blocking probability.展开更多
The goal of quality-of-service （QoS） multicast routing is to establish a multicast tree which satisfies certain constraints on bandwidth, delay and other metrics. The network state information maintained at every no...The goal of quality-of-service （QoS） multicast routing is to establish a multicast tree which satisfies certain constraints on bandwidth, delay and other metrics. The network state information maintained at every node is often im- precise in a dynamic environment because of non-negligible propagation delay of state messages, periodic updates due to overhead concern, and hierarchical state aggregation. The existing QoS multicast routing algorithms do not provide satisfactory performance with imprecise state information. We propose a distributed QoS multicast routing scheme based on traffic lights, called QMRI algorithm, which can probe multiple feasible tree branches, and select the optimal or near-optimal branch through the UR or TL mode for constructing a multicast tree with QoS guarantees if it exists. The scheme is designed to work with imprecise state information. The proposed algorithm considers not only the QoS requirements but also the cost optimality of the multicast tree. The correctness proof and the complexity analysis about the QMRI algorithm are also given. In addition, we develop NS2 so that it is able to simulate the imprecise network state information. Extensive simulations show that our algorithm achieves high call-admission ratio and low-cost multicast trees with modest message overhead.展开更多
文摘Dynamic multicast traffic grooming in wave-length division multiplexing(WDM)networks was analyzed to minimize networkwide costs and to increase the network resource utilization.A network model was developed for dynamic multicast traffic grooming with resource constraints and an algorithm that can provide quality of service(QoS)was proposed.The QoS is measured by the maximum number of lightpaths passing between the source and the destinations.The blocking probability of the algorithm was assessed in simulations.The results show that a higher QoS requirement results in higher blocking probability,and when the QoS requirement is low,changes in the QoS require-ments have only small effects on the blocking probability.
文摘The goal of quality-of-service （QoS） multicast routing is to establish a multicast tree which satisfies certain constraints on bandwidth, delay and other metrics. The network state information maintained at every node is often im- precise in a dynamic environment because of non-negligible propagation delay of state messages, periodic updates due to overhead concern, and hierarchical state aggregation. The existing QoS multicast routing algorithms do not provide satisfactory performance with imprecise state information. We propose a distributed QoS multicast routing scheme based on traffic lights, called QMRI algorithm, which can probe multiple feasible tree branches, and select the optimal or near-optimal branch through the UR or TL mode for constructing a multicast tree with QoS guarantees if it exists. The scheme is designed to work with imprecise state information. The proposed algorithm considers not only the QoS requirements but also the cost optimality of the multicast tree. The correctness proof and the complexity analysis about the QMRI algorithm are also given. In addition, we develop NS2 so that it is able to simulate the imprecise network state information. Extensive simulations show that our algorithm achieves high call-admission ratio and low-cost multicast trees with modest message overhead.
