We note that traditional markers don't consider the long term average rate and the instantaneous rate of traffic at the same time. Therefore, they can not achieve fair sharing excess bandwidth in proportion to Committed Information Rate(CIR). To solve these problems, we propose the Innovation Three Color Marker(ITCM) algorithm. Our proposed algorithm calculates both the long term average rate and the instantaneous rate of traffic when marking the packet. Moreover, ITCM achieves the proportional fair sharing among aggregates by marking the packet as yellow with probability in proportion to CIR. We have compared the performance of ITCM with traditional markers. Simulation results show that ITCM performs better than traditional markers in the case of under-subscription. It not only achieves the target rate, but also achieves proportional fairness of sharing the excess bandwidth.
In this paper, a novel congestion control for multimedia traffics in Metro Ethernet Networks known as Jitter-Based Congestion Control (JBCC) is proposed. The basic ideal of JBCC is that the jitter-corrupted multimedia packets are useless to the client and it is a waste of network resources to continue to forward these packets in the networks. JBCC improves the QoS of multimedia stream in Metro Ethernet Network by detecting and discarding packets that accumulated enough jitter so as to maintain a high bandwidth for packets that stay within the multimedia stream's jitter tolerance. Simulation results have shown that the proposed scheme can effectively lower the average received packet jitter than that using traditional congestion control algorithm RED and DropTail. Moreover, the proposed scheme can improve the useful goodput of the received packets when compared to RED and DropTail.
IP multicast suffers from scalability problems when the number of simultaneously active multicast groups is very large. In this paper, we propose an algorithm called SGTM (Scalable Group-Tree Match algorithm) which reduces the number of trees by allowing several groups to be aggregated to the same delivery tree. SGTM improves the state scalability because it can reduce the required multicast state and the management overhead for the distribution trees. The paper introduces metrics to measure multicast state and tree management overhead for multicast schemes. SGTM performs faster aggregations than previous aggregation algorithms by evaluating fewer trees for each group, while keeping the same performance. We then show the scalability and the fastness of SGTM by several simulations and we compare its performance to the previous algorithm.
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