We study an online caching problem in which requests can be served by a local cache to avoid retrieval costs from a remote server. The cache can update its state after a batch of requests and store an arbitrarily small fraction of each file. We study no-regret algorithms based on Online Mirror Descent (OMD) strategies. We show that the optimal OMD strategy depends on the request diversity present in a batch. We also prove that, when the cache must store the entire file, rather than a fraction, OMD strategies can be coupled with a randomized rounding scheme that preserves regret guarantees.
翻译:我们研究一个在线缓存问题, 本地缓存可以满足请求, 以避免从远程服务器上收回成本。 缓存可以在一系列请求后更新状态, 并存储每个文件的一小部分。 我们根据在线镜源( OMD) 战略研究无记录算法。 我们显示最佳 OMD 战略取决于批量中的请求多样性。 我们还证明, 当缓存必须存储整个文件而不是一个小部分时, OMD 战略可以与一个随机的圆环计划相结合, 以保存遗憾保证 。