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Bitrate Adaptation-aware Cache Partitioning for Video Streaming over Information-Centric Networks

机译:信息中心网络上用于视频流的比特率自适应感知缓存分区

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Recent studies suggest that performance gains for content delivery over Information-centric Networks (ICNs) may be negated by Dynamic Adaptive Streaming (DAS), the de facto method for retrieval of multimedia content. The bitrate adaptation mechanism that drives video streaming appears to clash with generic ICN caching techniques in ways that affect users' Quality of Experience (QoE). Cache performance diminishes as video consumers dynamically select content encoded at different bitrates. Motivated by preliminary evidence suggesting the merits of bitrate-based cache partitioning, we introduce a scheme to dissect the cache capacity of routers along a forwarding path according to dedicated bitrates. To facilitate this partitioning, we propose a guiding principle RippleCache, which stabilizes bandwidth fluctuation while achieving high cache utilization by safeguarding high-bitrate content on the edge and pushing low-bitrate content into the network core. We further propose a cache placement scheme, RippleFinder, to realize this RippleCache principle and highlight its impact on users' QoE by cache partitioning. The performance gains are reinforced by evaluations in NS-3. Measurements show RippleFinder can significantly reduce bitrate oscillation, while ensuring high video quality, indicating overall improvement to QoE.
机译:最近的研究表明,通过动态自适应流(DAS)可以抵消以信息为中心的网络(ICN)上的内容传递的性能提高,而动态自适应流(DAS)是事实上的多媒体内容检索方法。驱动视频流的比特率自适应机制似乎与通用的ICN缓存技术发生冲突,从而影响了用户的体验质量(QoE)。由于视频使用者动态选择以不同比特率编码的内容,因此缓存性能会下降。出于初步证据表明基于比特率的缓存分区的优点的启发,我们引入了一种根据专用比特率剖析转发路径上路由器缓存容量的方案。为了促进这种划分,我们提出了一个指导原则RippleCache,它通过保护边缘上的高比特率内容并将低比特率内容推入网络核心来稳定带宽波动,同时实现高缓存利用率。我们进一步提出了一种缓存放置方案RippleFinder,以实现此RippleCache原理,并通过缓存分区突出显示其对用户的QoE的影响。通过在NS-3中进行评估,增强了性能提升。测量表明,RippleFinder可以显着降低比特率振荡,同时确保高视频质量,表明QoE总体上得到了改善。

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