In typical coded caching scenarios, the content of a central library is assumed to be of interest to all receiving users. However, in a realistic scenario the users may have diverging interests which may intersect to various degrees. What happens for example if each file is of potential interest to, say, $40\,\%$ of the users and each user has potential interest in $40\,\%$ of the library? What if then each user caches selfishly only from content of potential interest? In this work, we formulate the symmetric selfish coded caching problem, where each user naturally makes requests from a subset of the library, which defines its own file demand set (FDS), and caches selfishly only contents from its own FDS. For the scenario where the different FDSs symmetrically overlap to some extent, we propose a novel information-theoretic converse that reveals, for such general setting of symmetric FDS structures, that selfish coded caching yields a load performance which is strictly worse than that in standard coded caching.
翻译:在典型的编码缓存情景中,中央图书馆的内容被假定为所有接收用户都感兴趣。 但是,在现实情况下,用户可能有不同的利益差异,这些利益可能在不同程度上相互交叉。 例如,如果每个文件都可能有兴趣,比如,40美元,用户和每个用户的$ 美元对40美元,图书馆的$ 美元有潜在兴趣? 如果每个用户只自私地从潜在感兴趣的内容中隐藏起来,那又如何? 在这项工作中,我们提出对称自私的编码缓存问题,每个用户自然地从图书馆的一个子组中提出要求,该组界定了自己的文件需求组(FDS),并且自私地从自己的FDS中隐藏只隐藏内容。对于不同FDS对称重叠的情况,我们建议一个新的信息-理论连接,在对称 FDS结构的总体设置中,自私的编码缓存产生一个绝对不如标准编码缓存的负荷性能。