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Predictive resource allocation for real time video traffic in broadband satellite networks

机译:宽带卫星网络中实时视频流量的预测性资源分配

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Satellites are attractive for broadband networks because they provide fairly hgih bit-rate connections over a wide area. However, satellite networks are characterised by having a fixed amount of shared bandwidth between all users, and by relativel ylarge propagation delays. These problems pose a challenge when implementing a high performance dynamic resource allocation scheme to effectively share the bandwidth among a large population of Earth terminals, with heterogeneous mix of traffic and different QOS requirements. This paper proposes the implementation of a predictive resource allocation scheme for the real time video component of the traffic in a broadband satellite network environment. Two predictive implementations are investigated: one based on time series analysis, and the other based on neural networks.
机译:卫星对宽带网络很有吸引力,因为它们在宽广的区域内提供相当高的比特率连接。然而,卫星网络的特征在于在所有用户之间具有固定数量的共享带宽,并且具有相对较大的传播延迟。在实施高性能动态资源分配方案以在大量的地球终端之间有效地共享带宽,流量的异构混合和不同的QOS要求时,这些问题构成了挑战。本文提出了一种在宽带卫星网络环境中针对流量实时视频分量的预测性资源分配方案的实现。研究了两种预测性实现:一种基于时间序列分析,另一种基于神经网络。

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