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arXiv 2102.04322cs.ITcs.DCmath.IT
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分布式存储分配以实现最佳服务速率

Distributed Storage Allocations for Optimal Service Rates

Pei Peng, Moslem Noori, Emina Soljanin

摘要:

冗余存储在各种形式的不确定性下维持分布式系统的性能。本文考虑了节点访问和下载服务的不确定性。我们考虑两种下载服务模型下的两种访问模型。在一种访问模型中,用户可以以固定的概率访问每个节点,而在另一种访问模型中,用户可以访问随机的固定大小的节点子集。我们考虑两个下载服务模型。在第一个(小文件)模型中,与文件大小相关的随机性可以忽略不计。在第二种(大文件)模型中,随机性与文件大小和系统操作都相关。我们关注系统的服务率。对于固定的冗余级别,系统的服务速率由存储节点上的编码块的分配来确定。我们考虑准均匀分配,其中编码内容均匀分布在节点的子集之间。我们要解决的问题是这个子集(扩展)的大小应该是多少。我们表明,在小文件模型中,集中的编码内容的最小尺寸的子集是普遍最优的。对于大文件模型,最佳散布取决于系统参数。这些结论适用于两种访问模式。

英文摘要:

Redundant storage maintains the performance of distributed systems under various forms of uncertainty. This paper considers the uncertainty in node access and download service. We consider two access models under two download service models. In one access model, a user can access each node with a fixed probability, and in the other, a user can access a random fixed-size subset of nodes. We consider two download service models. In the first (small file) model, the randomness associated with the file size is negligible. In the second (large file) model, randomness is associated with both the file size and the system's operations. We focus on the service rate of the system. For a fixed redundancy level, the systems' service rate is determined by the allocation of coded chunks over the storage nodes. We consider quasi-uniform allocations, where coded content is uniformly spread among a subset of nodes. The question we address asks what the size of this subset (spreading) should be. We show that in the small file model, concentrating the coded content to a minimum-size subset is universally optimal. For the large file model, the optimal spreading depends on the system parameters. These conclusions hold for both access models.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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