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Clustering and Constraints for Real-time Multicast

机译:实时多播的聚类和约束

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Real-time multicast is widely applied on Internet. Unfortunately, current systems share the same problem that they are not able to maintain high and stable performance when the scale grows unexpectedly large or the nodes' performance fluctuation drastically. This paper attempts to solve the problem by means of network structure clustering and constraints. We show that the multicast network can achieve much higher optimizing speed through dynamically clustering nodes with similar performance records. We propose a cluster-based multicast model and constraints on it. We further provide Regular-Balanced constraint as the recommended constraint, which is related to higher ability of scale and failure tolerance. We also test our model by contrast experiments with CoolStreaming and NICE.
机译:实时多播广泛应用于互联网。遗憾的是,当前系统分享了同样的问题,即当规模大大大或节点的性能波动大幅增加时,它们无法保持高稳定的性能。本文试图通过网络结构聚类和约束来解决问题。我们表明,通过动态聚类具有相似性能记录的节点,多播网络可以通过动态聚类来实现更高的优化速度。我们提出了一种基于群集的多播模型和限制。我们进一步提供定期平衡的约束作为推荐的约束,与更高的规模和失效耐受能力有关。我们还通过对比的实验用凉爽的实验来测试我们的模型。

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