具有异步需求的观众保留率感知缓存和编码视频交付
Audience-Retention-Rate-Aware Caching and Coded Video Delivery with Asynchronous Demands
摘要：
编码缓存的大多数结果都集中在静态场景上，其中固定数量的用户同步地从内容库中放置他们的请求，并且性能是根据满足所有这些需求的延迟来衡量的。然而，在实践中，用户随着时间异步地开始观看在线视频内容，并且经常在视频完成之前中止观看视频。后一种行为是通过观众留存率的概念来捕捉的，观众留存率衡量的是平均观看的视频内容的部分。为了使编码缓存更接近实践，本文考虑了异步用户需求，允许用户需求随着时间的推移随机到达，并考虑了视频文件的受欢迎程度和观众保留率。提出了一种分散的部分编码缓存（PCC）方案，以及两种缓存分配方案，即最优缓存分配（OCA）和基于流行度的缓存分配（PCA），它们将用户的缓存分配到库中视频文件的不同块中。数值结果验证了建议的PCC计划，无论是与OCA或PCA，优于传统的未编码的缓存，以及国家的最先进的分散式缓存计划，只考虑文件的流行程度，并设计用于同步需求到达。还提出了一个信息理论上的平均交付率的下限。
英文摘要：
Most results on coded caching focus on a static scenario, in which a fixed number of users synchronously place their requests from a content library, and the performance is measured in terms of the latency in satisfying all of these demands. In practice, however, users start watching an online video content asynchronously over time, and often abort watching a video before it is completed. The latter behaviour is captured by the notion of audience retention rate, which measures the portion of a video content watched on average. In order to bring coded caching one step closer to practice, asynchronous user demands are considered in this paper, by allowing user demands to arrive randomly over time, and both the popularity of video files, and the audience retention rates are taken into account. A decentralized partial coded caching (PCC) scheme is proposed, together with two cache allocation schemes; namely the optimal cache allocation (OCA) and the popularity-based cache allocation (PCA), which allocate users' caches among different chunks of the video files in the library. Numerical results validate that the proposed PCC scheme, either with OCA or PCA, outperforms conventional uncoded caching as well as the state-of-the-art decentralized caching schemes, which consider only the file popularities, and are designed for synchronous demand arrivals. An information-theoretical lower bound on the average delivery rate is also presented.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
