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Sharing Cache Resources Among Content Providers: A Utility-Based Approach

机译:共享内容提供者之间的缓存资源:基于实用程序的方法

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In this paper, we consider the problem of allocating cache resources among multiple content providers. The cache can be partitioned into slices and each partition can be dedicated to a particular content provider or shared among a number of them. It is assumed that each partition employs the least recently used policy for managing content. We propose utility-driven partitioning, where we associate with each content provide a utility that is a function of the hit rate observed by the content provider. We consider two scenarios: 1) content providers serve disjoint sets of files and 2) there is some overlap in the content served by multiple content providers. In the first case, we prove that cache partitioning outperforms cache sharing as cache size and a number of contents served by providers go to infinity. In the second case, it can be beneficial to have separate partitions for overlapped content. In the case of two providers, it is usually always beneficial to allocate a cache partition to serve all overlapped content and separate partitions to serve the non-overlapped contents of both providers. We establish conditions when this is true asymptotically but also present an example where it is not true asymptotically. We develop online algorithms that dynamically adjust partition sizes in order to maximize the overall utility and prove that they converge to optimal solutions, and through numerical evaluations we show they are effective.
机译:在本文中,我们考虑在多个内容提供商之间分配缓存资源的问题。高速缓存可以分成切片,每个分区可以专用于特定内容提供者或在许多时间内共享。假设每个分区采用最近最近使用的策略来管理内容。我们提出了实用程序驱动的分区,其中我们与每个内容相关联提供了一个实用程序,该实用程序是内容提供商观察到的命中率的函数。我们考虑两种情况:1)内容提供商提供不相交的文件集和2)在多个内容提供商服务的内容中存在一些重叠。在第一种情况下,我们证明了高速缓存分区优先表达高速缓存共享作为高速缓存大小和提供者服务的许多内容转到无穷大。在第二种情况下,对于重叠内容具有单独的分区可能是有益的。在两个提供商的情况下,分配高速缓存分区通常总是有益的,以用于所有重叠的内容和单独的分区以提供两个提供商的非重叠内容。我们建立条件,当这是真正的渐近,但也呈现一个例子,其中它不是真实的。我们开发在线算法,动态调整分区大小,以最大限度地提高整个实用程序,并证明它们收敛到最佳解决方案,并通过我们显示的数字评估是有效的。

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