Algorithms for asynchronous coded caching

H. Ghasemi, A. Ramamoorthy
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引用次数: 5

Abstract

The original formulation of the coded caching problem assumes that the file requests from the users are synchronized, i.e., they arrive at the server at the same time. Several subsequent contributions work under the same assumption. Furthermore, the majority of prior work does not consider a scenario where users have deadlines. In our previous work we formulated the asynchronous coded caching problem where user requests arrive at different times. Furthermore, the users have specified deadlines. We proposed a linear program for obtaining its optimal solution. However, the size of the LP (number of constraints and variables) grows rather quickly with the number of users and cache sizes. In this work, we explore a dual decomposition based approach for solving the LP under consideration. We demonstrate that the dual function can be evaluated by equivalently solving a number of minimum cost network flow algorithms. Minimum cost network flow algorithms have been the subject of much investigation and current solvers routinely solve instances with millions of nodes in minutes. Our proposed approach leverages these fast solvers and allows us to solve several large scale instances of the asynchronous coded caching problem with manageable time and memory complexity.
异步编码缓存算法
编码缓存问题的原始公式假设来自用户的文件请求是同步的,也就是说,它们同时到达服务器。随后的几个贡献在相同的假设下工作。此外,大多数先前的工作没有考虑用户有最后期限的场景。在我们之前的工作中,我们制定了异步编码缓存问题,其中用户请求在不同时间到达。此外,用户还指定了截止日期。提出了求解其最优解的线性规划。然而,LP的大小(约束和变量的数量)随着用户数量和缓存大小的增加而快速增长。在这项工作中,我们探索了一种基于对偶分解的方法来解决所考虑的LP。我们证明了对偶函数可以通过等价地求解一些最小代价网络流算法来评估。最小代价网络流算法一直是许多研究的主题,目前的求解器通常在几分钟内解决具有数百万节点的实例。我们提出的方法利用了这些快速求解器,并允许我们以可管理的时间和内存复杂性来解决异步编码缓存问题的几个大规模实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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