Mean-field-analysis of coding versus replication in cloud storage systems
Mean-field-analysis of coding versus replication in cloud storage systems
复制标题
云存储系统中编码与复制的平均场分析
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
R. Srikant
中科院分区：
文献类型：
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作者：
Bin Li;A. Ramamoorthy;R. Srikant
我们研究云存储系统，其中大量文件存储在大量服务器中。在这样的系统中，文件要么被复制或编码以确保可靠性，即从服务器失败中恢复文件。可以进一步利用存储中的这种冗余，以通过适当的负载平衡（路由）方案来提高系统性能（平均文件访问延迟）。但是，从系统性能的角度来看，尚不清楚编码或复制是否更好，因为通常对此类系统的相应排队分析非常困难，除非系统渐近地负载倾向于零。在这里，我们研究了系统负载不是渐近零的更困难的情况。使用系统大小很大的事实，我们获得了在每个服务器上等待的文件访问请求数量的稳态分布的平均范围限制。然后，我们使用平均场限制来表明，对于每个文件给定的存储容量，编码在所有流量负载下严格胜过复制，同时提高可靠性。此外，重量流量的绩效提高的因素至少与流量流量的情况一样大。最后，我们通过广泛的模拟来验证这些结果。
We study cloud-storage systems with a very large number of files stored in a very large number of servers. In such systems, files are either replicated or coded to ensure reliability, i.e., file recovery from server failures. This redundancy in storage can further be exploited to improve system performance (mean file access delay) through appropriate load-balancing (routing) schemes. However, it is unclear whether coding or replication is better from a system performance perspective since the corresponding queueing analysis of such systems is, in general, quite difficult except for the trivial case when the system load asymptotically tends to zero. Here, we study the more difficult case where the system load is not asymptotically zero. Using the fact that the system size is large, we obtain a mean-field limit for the steady-state distribution of the number of file access requests waiting at each server. We then use the mean-field limit to show that, for a given storage capacity per file, coding strictly outperforms replication at all traffic loads while improving reliability. Further, the factor by which the performance improves in the heavy-traffic is at least as large as in the light-traffic case. Finally, we validate these results through extensive simulations.