We consider a distributed storage system which stores several hot (popular) and cold (less popular) data files across multiple nodes or servers. Hot files are stored using repetition codes while cold files are stored using erasure codes. The nodes are prone to failure and hence at any given time, we assume that only a fraction of the nodes are available. Using a cavity process based mean field framework, we analyze the download time for users accessing hot or cold data in the presence of failed nodes. Our work also illustrates the impact of the choice of the storage code on the download time performance of users in the system.
翻译：我们考虑的是一个分布式存储系统,它储存多个节点或服务器上的若干热(大众)和冷(不受欢迎的)数据文件。热文件用重复代码存储,而冷文件则用消除代码存储。节点容易出故障,因此在任何特定时间,我们假设只有一小部分节点可用。我们使用基于洞穴的默认字段框架,分析用户在节点失败时获取热或冷数据的时间。我们的工作还说明了选择存储代码对系统用户下载时间性能的影响。
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