Right-Sizing Geo-distributed Data Centers for Availability and Latency
Right-Sizing Geo-distributed Data Centers for Availability and Latency
复制标题
调整地理分布式数据中心的规模以提高可用性和延迟
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
A. Sivasubramaniam
中科院分区：
文献类型：
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作者：
Iyswarya Narayanan;A. Kansal;A. Sivasubramaniam
我们向云开发人员展示如何为部署在多个兆瓦 DC 上的地理分布式应用程序调整数据中心 (DC) 容量，也可能使用许多较小的边缘 DC。请注意，地理分布式基础设施的容量注意事项不会分解为单独的 DC 容量规划。使用边缘 DC 时，异构可用性和成本会影响边缘 DC 和核心 DC 之间的容量分配。客户端的不均匀空间分布以及延迟和可用性约束之间的相互依赖性使得在每个 DC 上配置正确的容量变得非常重要。我们开发了一个地理分布式容量规划框架，以捕获影响容量的关键因素，包括应用程序需求模式、延迟和可用性要求、数据中心成本可用性权衡以及数据复制开销。我们将我们的框架应用于实际的应用程序和数据中心基础设施设置，以收集关于如何跨数据中心配置和分配容量以满足一组代表性要求和成本的见解。
We show cloud developers how to right size data center (DC) capacity for geo-distributed applications deployed on several multi-megawatt DCs, possibly also using many smaller edge DCs. Note that capacity considerations for a geo-distributed infrastructure do not decompose into individual DC capacity planning. When edge DCs are used, heterogeneous availability and costs affect the capacity split between the edge and core DCs. Non-uniform spatial distribution of clients and interdependence between latency and availability constraints make it non-trivial to provision the right capacity at each DC. We develop a geo-distributed capacity planning framework to capture the key factors that influence capacity, ranging from application demand patterns, latency and availability requirements, DC cost-availability trade-offs, and data replication overheads. We apply our framework to a realistic application and DC infrastructure setting to gather insights into how capacity should be provisioned and allocated across DCs for a representative set of requirements and costs.