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Network Coding Node Placement for Delay Minimization in Streaming Overlays

机译:网络编码节点放置,用于流重叠中的延迟最小化

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Network coding has been proposed recently as an efficient method to increase network throughput by allowing network nodes to combine packets instead of simply forwarding them. However, packet combinations in the network may increase delay, complexity and even generate overly redundant information when they are not designed properly. Typically, the best performance is not achieved when all the nodes perform network coding. In this paper, we address the problem of efficiently placing network coding nodes in overlay networks, so that the rate of innovating packets is kept high, and the delay for packet delivery is kept small. We first estimate the expected number of duplicated packets in each network node. These estimations permit to select the nodes that should implement network coding, so that the innovating rate increases. Two algorithms are then proposed for the cases where a central node is aware of the full network statistics and where each node knows the local statistics from its neighbor, respectively. The simulation results show that in the centralized scenario the maximum profit from network coding comes by adding only a few network coding nodes. A similar result is obtained with the algorithm based on local statistics, which moreover performs very close to the centralized solution. These results show that the proper selection of the network coding nodes is crucial for minimizing the transmission delay in streaming overlays.
机译:最近,网络编码已被提出为一种有效的方法,可以通过允许网络节点组合数据包而不是简单地转发数据包来增加网络吞吐量。但是,如果设计不当,网络中的数据包组合可能会增加延迟,复杂性,甚至会生成过多的冗余信息。通常,当所有节点都执行网络编码时,无法获得最佳性能。在本文中,我们解决了将网络编码节点有效地放置在覆盖网络中的问题,从而使数据包的创新率保持较高,而使数据包传递的延迟保持较小。我们首先估计每个网络节点中预期的重复数据包数量。这些估计允许选择应实施网络编码的节点,从而提高创新率。然后针对中心节点了解完整的网络统计信息以及每个节点分别从其邻居了解本地统计信息的情况,提出了两种算法。仿真结果表明,在集中式方案中,仅添加几个网络编码节点即可最大程度地提高网络编码的收益。使用基于本地统计信息的算法可获得相似的结果,此外,该算法与集中式解决方案的性能非常接近。这些结果表明,网络编码节点的正确选择对于最小化流媒体覆盖中的传输延迟至关重要。

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