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 content. 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 content, 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, 并存储每个内容的任意一小部分 。 我们根据在线镜源( OMD) 策略研究无回报算法 。 我们显示最佳 OMD 策略取决于批量中的请求多样性 。 我们还证明, 当缓存必须存储全部内容而不是一个小部分时, 缓存策略可以与随机组合计划相结合, 以保留遗憾保证 。