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.
Bibliographical noteFunding Information:
Manuscript received December 25, 2017; revised July 6, 2018; accepted December 2, 2018; approved by IEEE/ACM TRANSACTIONS ON NETWORK-ING Editor R. Lo Cigno. Date of publication February 13, 2019; date of current version April 16, 2019. This work was supported in part by the National Natural Science Foundation of China under Grant 61502393, in part by the Natural Science Basic Research Plan in Shaanxi Province of China under Grant 2017JM6066, in part by the Fundamental Research Funds for the Central Universities under Grant 3102017zy031, and in part by the National Science Foundation under Grant CNS-1413998, Grant CNS-1617437, Grant CNS-1411636, Grant CNS-1618339, and Grant CNS-1617729. (Corresponding author: Weibo Chu.) M. Dehghan is with Google Inc., Cambridge, MA 02142 USA (e-mail: email@example.com).
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- Content providers
- cache partitioning
- cache sharing
- online partitioning