Tackling heterogeneous traffic in multi-access systems via erasure coded servers
Tackling heterogeneous traffic in multi-access systems via erasure coded servers
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DOI：
10.1145/3492866.3549713
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Tuhinangshu Choudhury;Weina Wang;Gauri Joshi
中科院分区：
文献类型：
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作者：
Tuhinangshu Choudhury;Weina Wang;Gauri Joshi
现代应用程序生成的大部分数据存储在云中，访问这些数据并使用它们执行计算的作业数量呈指数级增长。数据访问或计算作业的数量在不同的作业类型中可能是不同的，并且可能会随着时间的推移而发生不可预测的变化。云服务提供商通过过度配置托管每种作业类型的服务器数量来应对这种需求异构性和不可预测性。在本文中，我们提出增加擦除编码服务器，它可以在不增加存储开销的情况下灵活地服务于多个作业类型。我们分析了这种擦除编码系统的服务容量区域和响应时间，并将它们与目前云中使用的标准非编码复制系统进行了比较。我们表明，编码扩展了服务容量区域，从而使系统能够处理不同数据类型的需求变化。此外，我们还刻画了编码系统在不同到达速率下的响应时间。这一分析表明，即使添加少量编码的服务器也可以显著缩短平均响应时间，在不同工作类型之间需求不一致的情况下，可以大幅缩短响应时间。
Most data generated by modern applications is stored in the cloud, and there is an exponential growth in the volume of jobs to access these data and perform computations using them. The volume of data access or computing jobs can be heterogeneous across different job types and can unpredictably change over time. Cloud service providers cope with this demand heterogeneity and unpredictability by over-provisioning the number of servers hosting each job type. In this paper, we propose the addition of erasure-coded servers that can flexibly serve multiple job types without additional storage cost. We analyze the service capacity region and the response time of such erasure-coded systems and compare them with standard uncoded replication-based systems currently used in the cloud. We show that coding expands the service capacity region, thus enabling the system to handle variability in demand for different data types. Moreover, we characterize the response time of the coded system in various arrival rate regimes. This analysis reveals that adding even a small number of coded servers can significantly reduce the mean response time, with a drastic reduction in regimes where the demand is skewed across different job types.