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.

翻译：重复存储会维持分布式系统在各种形式不确定性下的性能。 本文考虑了节点访问和下载服务的不确定性。 我们考虑两个下载服务模式下的两种访问模式。 在一种访问模式中, 用户可以以固定概率访问每个节点, 而在另一种模式中, 用户可以访问随机固定大小的节点子。 我们考虑两种下载服务模式。 在第一种( 小文件) 模式中, 文件大小的随机性是微不足道的。 在第二种( 大文件) 模式中, 随机性与文件大小和系统操作都相关。 我们侧重于系统的服务率。 对于固定冗余级别, 系统服务率由存储节点上的编码块分配决定。 我们考虑准统一配置, 编码内容在一组节点中统一分布。 我们所处理的问题是, 这个子集( 扩展) 的大小应该是多少。 我们在第二个( 大文件) 模式中显示, 将编码内容集中到一个最小尺寸的子群点。 对于大文件模式来说, 最理想的扩展率取决于系统的参数 。