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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Ephemeral Content Popularity at the Edge and Implications for On-Demand Caching
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Ephemeral Content Popularity at the Edge and Implications for On-Demand Caching

机译：边缘的临时内容受欢迎程度及其对按需缓存的影响

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摘要

The ephemeral content popularity seen with many content delivery applications can make indiscriminate on-demand caching in edge networks highly inefficient, since many of the content items that are added to the cache will not be requested again from that network. In this paper, we address the problem of designing and evaluating more selective edge-network caching policies. The need for such policies is demonstrated through an analysis of a dataset recording YouTube video requests from users on an edge network over a 20-month period. We then develop a novel workload modelling approach for such applications and apply it to study the performance of alternative edge caching policies, including indiscriminate caching and cache on kk th request for different kk . The latter policies are found able to greatly reduce the fraction of the requested items that are inserted into the cache, at the cost of only modest increases in cache miss rate. Finally, we quantify and explore the potential room for improvement from use of other possible predictors of further requests. We find that although room for substantial improvement exists when comparing performance to that of a perfect “oracle” policy, such improvements are unlikely to be achievable in practice.
机译：在许多内容交付应用程序中看到的短暂的内容流行性可能使边缘网络中不加选择的按需缓存效率极低，因为添加到缓存中的许多内容项都不会再次从该网络中请求。在本文中，我们解决了设计和评估更具选择性的边缘网络缓存策略的问题。通过对记录20个月内来自边缘网络上用户的YouTube视频请求的数据集进行分析，证明了对此类政策的需求。然后，我们为此类应用程序开发一种新颖的工作负载建模方法，并将其应用于研究替代性边缘缓存策略的性能，包括不加区别的缓存和针对不同kk的kk请求的缓存。发现后一种策略能够以仅适度增加高速缓存未命中率的代价来大大减少插入高速缓存中的所请求项的比例。最后，我们量化并探索通过使用其他可能的进一步请求的预测因素来改进的潜在空间。我们发现，尽管将性能与完善的“ oracle”策略进行比较时仍存在实质性改进的空间，但实际上这种改进不太可能实现。

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