A promising research area that has recently emerged, is on how to use index coding to improve the communication efficiency in distributed computing systems, especially for data shuffling in iterative computations. In this paper, we posit that pliable index coding can offer a more efficient framework for data shuffling, as it can better leverage the many possible shuffling choices to reduce the number of transmissions. We theoretically analyze pliable index coding under data shuffling constraints, and design a hierarchical data-shuffling scheme that uses pliable coding as a component. We find benefits up to $O(ns/m)$ over index coding, where $ns/m$ is the average number of workers caching a message, and $m$ , $n$ , and $s$ are the numbers of messages, workers, and cache size, respectively.

中文翻译：

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数据混洗的灵活索引编码方法

最近出现的一个有前途的研究领域是如何使用索引编码来提高分布式计算系统中的通信效率，尤其是迭代计算中的数据混洗。在本文中，我们假设柔韧的索引编码可以为数据混洗提供更有效的框架，因为它可以更好地利用许多可能的混洗选择来减少传输次数。我们从理论上分析了数据混洗约束下的柔韧索引编码，并设计了一种以柔韧编码为组件的分层数据混洗方案。我们发现好处高达 $O(ns/m)$ 过索引编码，其中 $ns/m$ 是缓存消息的平均工人数，和 百万美元 , $n$ ， 和 $s$ 分别是消息数、工作者数和缓存大小。