Decentralized coded caching scheme, introduced by Maddah-Ali and Niesen, assumes that the caches are filled with no coordination. This work identifies a decentralized coded caching scheme -- under the assumption of uncoded placement -- for shared cache network, where each cache serves multiple users. Each user has access to only a single cache and the number of caches is less than or equal to the number of users. For this setting, we derive the optimal worst-case delivery time for any user-to-cache association profile where each such profile describes the number of users served by each cache. The optimality is shown using an index-coding based converse. Further, we improve the delivery scheme to accommodate redundant demands. Also, an optimal linear error correcting delivery scheme is proposed for the worst-case demand scenario. Next, we consider the Least Recently Sent (LRS) online coded caching scheme where the caches need to be updated based on the sequence of demands made by the users. Cache update happens if any of the demanded file was not partially cached at the users. The update is done by replacing the least recently sent file with the new file. But, the least recently sent file need not be unique. In that case, there needs to be some ordering of the files which are getting partially cached, or else centralized coordination would have to be assumed which does not exist. If each user removes any of the least recently used files at random, then the next delivery phase will not serve the purpose. A modification is suggested for the scheme by incorporating an ordering of files. Moreover, all the above results with shared caches are extended to the online setting.
翻译:Maddah- Ali 和 Niesen 推出的分层代码缓存方案, 假设由Maddah- Ali 和 Niesen 推出, 假设缓存的用户数量没有协调地填充缓存。 这项工作为共享缓存网络确定了一个分散的编码缓存方案 -- -- 在未编码的放置假设下 -- -- 每个缓存都为多个用户服务。 每个用户只能访问单一缓存, 缓存数量小于或等于用户数量。 对于此设置, 我们为任何用户对缓存的关联配置获取最坏的交付时间。 每个用户对缓存的配置描述每个用户服务用户数量。 优化的缓存显示为优化, 使用基于基于索引编码的对调试, 并且我们改进交付计划以适应冗余需求。 此外, 最优的线性修正交付计划是针对最短的线性错误。 下一步, 我们考虑最小的缓存计划需要根据用户的需求来更新。 假设, 任何需要的修改文件都会部分缓存在用户中出现。 更新后, 将使用最近发送的交付文件替换最近发送的最小的版本文件, 需要重新整理到新版本, 。 需要的是, 保存为最小的中央化为最小的版本。 。