Caching content on mobile devices reduces not only the transmission of backhaul links but also the latency of content acquisition. However, in the existing caching schemes, the joint effect of the caching-aware indicator of users and content dimensions on the caching strategy is not considered. Thus, how to learn fine-grained caching- aware indicators and design caching schemes are still challenging issues. In order to solve these problems, in this article, we first propose the cognitive caching architecture and give the fine-grained caching-aware indicators metric. Then we design a cognitive caching scheme that includes what to do in cognitive caching and how to do cognitive caching. Finally, experimental results show that the proposed cognitive caching scheme is superior to other caching schemes in terms of learning regret and caching cost.

中文翻译：

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认知缓存：通过学习细粒度的缓存感知指标来进行认知无线移动缓存

在移动设备上缓存内容不仅可以减少回程链路的传输，还可以减少内容获取的延迟。但是，在现有的缓存方案中，没有考虑用户的缓存感知指示器和内容维度对缓存策略的联合影响。因此，如何学习细粒度的缓存感知指标和设计缓存方案仍然是具有挑战性的问题。为了解决这些问题，在本文中，我们首先提出了认知缓存体系结构，并给出了细粒度的缓存感知指标指标。然后，我们设计一种认知缓存方案，其中包括在认知缓存中执行的操作以及如何进行认知缓存。最后，实验结果表明，提出的认知缓存方案在学习遗憾和缓存成本方面优于其他缓存方案。