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Impact of caching on HTTP Adaptive Streaming decisions: Towards an optimal

机译:缓存对HTTP自适应流决策的影响:实现最佳化

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The interplay between caching and HTTP Adaptive Streaming (HAS) is known to be intricate, and possibly detrimental to QoE. In this paper, we make the case for caching-aware rate decision algorithms at the client side which do not require any collaboration with cache or server. To this goal, we introduce the optimization model which allows to compute the optimal rate decisions in the presence of cache, and compare the current main representatives of HAS algorithms (RBA and BBA) to this optimal. This allows us to assess how far from the optimal these versions are, and on which to build a caching-aware rate decision algorithm.
机译:众所周知,缓存和HTTP自适应流(HAS)之间的相互作用非常复杂,并且可能对QoE不利。在本文中,我们为不需要客户端与缓存或服务器协作的客户端感知缓存的速率决策算法提供了依据。为此,我们引入了优化模型,该模型允许在存在缓存的情况下计算最优速率决策,并将当前HAS算法(RBA和BBA)的主要代表与该最优模型进行比较。这使我们能够评估这些版本与最佳版本之间的距离,以及在哪个版本上构建可感知缓存的速率决策算法。

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