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首页> 外文期刊>Computer Communications >Fast And Proximity-aware Multi-source Overlay Multicast Under Heterogeneous Environment
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Fast And Proximity-aware Multi-source Overlay Multicast Under Heterogeneous Environment

机译:异构环境下快速且可感知近距离的多源覆盖组播

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Overlay multicast has been considered as one of the most important developments for the next generation Internet infrastructure. In this paper, we consider overlay multicast in the scenarios where any participant node is a potential data source. Existing multicast algorithms for single-source always require a long time to deliver messages or have high maintenance overhead when multiple data sources are allowed. There are other algorithms that are designed for multi-source scenarios. But they consume too much network resources and have a long convergence time because of proximity ignorance. To address the issues, we present FPCast, which leverages node heterogeneity and proximity information at the same time. Physically close nodes are grouped into clusters and each cluster selects a powerful, stable node as its rendezvous point. The rendezvous nodes form a DHT-based structure. Data messages are replicated and forwarded along implicit, source specific, and heterogeneity-aware multicast trees. We further reduce the delivery delay by introducing probabilistic forwarding scheme. We show the average delivery path length converges to O(logn) automatically (n is the number of nodes in the overlay). The simulation results demonstrate the superiority of our algorithm in terms of message delivery time and network resource consumption, in comparison with the previous randomized algorithms. The algorithm is also resilient to node failures.
机译:覆盖多播已被视为下一代Internet基础结构的最重要发展之一。在本文中,我们考虑在任何参与者节点都是潜在数据源的情况下进行覆盖多播。当允许多个数据源时,用于单源的现有多播算法始终需要较长的时间来传递消息,或者维护成本较高。还有其他针对多源方案设计的算法。但是由于邻近性的无知,它们消耗了太多的网络资源并且收敛时间很长。为了解决这些问题,我们提出了FPCast,它同时利用了节点异构性和邻近性信息。物理上接近的节点被分组为群集,并且每个群集都选择一个功能强大且稳定的节点作为其集合点。集合节点形成基于DHT的结构。数据消息将沿隐式,特定于源且了解异构性的多播树进行复制和转发。通过引入概率转发方案,我们进一步减少了交付延迟。我们显示平均传送路径长度自动收敛到O(logn)(n是覆盖中的节点数)。与以前的随机算法相比,仿真结果证明了我们的算法在消息传递时间和网络资源消耗方面的优越性。该算法还可以抵抗节点故障。

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