大型分布式缓存中的内容复制

Sharayu Moharir, N. Karamchandani
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引用次数: 15

摘要

在本文中,我们考虑了分布式缓存系统中内容复制和请求路由的算法任务,该系统由中央服务器和大量缓存组成,每个缓存都具有有限的存储和服务能力。我们研究了一个时隙系统,在每个时隙中,大量的请求必须与大量的缓存相匹配,其中每个请求可以由存储请求内容的任何缓存提供服务。所有不能由缓存提供服务的请求都通过从中央服务器获取请求的内容来提供服务。目标是最小化来自中央服务器的传输速率。我们使用内容复制问题和背包问题之间的新映射来证明任何内容复制策略的传输速率的下界。利用从映射中获得的见解,我们提出了一个内容复制策略——背包存储——它实现了这个下限。虽然在大量缓存中复制最流行的内容在直觉上是有意义的,但令人惊讶的是,在某些情况下,backpack Storage策略根本不选择在缓存中复制最流行的内容。
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Content replication in large distributed caches
In this paper, we consider the algorithmic task of content replication and request routing in a distributed caching system consisting of a central server and a large number of caches, each with limited storage and service capabilities. We study a time-slotted system where in each time-slot, a large batch of requests has to be matched to a large number of caches, where each request can be served by any cache which stores the requested content. All requests which cannot be served by the caches are served by fetching the requested content from the central server. The goal is to minimize the transmission rate from the central server. We use a novel mapping between our content replication problem and the Knapsack problem to prove a lower bound on the transmission rate for any content replication policy. Using insights obtained from the mapping, we propose a content replication policy — Knapsack Storage — which achieves this lower bound. While it intuitively makes sense to replicate the more popular contents on a larger number of caches, surprisingly, in certain cases, the Knapsack Storage policy chooses not to replicate the most popular contents on the caches at all.
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