Probabilistic Modeling of Computing Demand for Service Level Agreement

被引:3
|
作者
Shenoy, Saahil [1 ]
Gorinevsky, Dimitry [1 ,2 ]
Laptev, Nikolay [3 ,4 ]
机构
[1] Stanford Univ, Stanford, CA 94305 USA
[2] Mitek Analyt LLC, Palo Alto, CA 94306 USA
[3] Yahoo Labs, Sunnyvale, CA 94089 USA
[4] Uber, San Francisco, CA 94102 USA
关键词
Resource management; Data models; Computational modeling; Probabilistic logic; Load modeling; Maximum likelihood estimation; Time series analysis; Extreme value theory (EVT); cloud computing; resource allocation; bayesian statistics; SLA;
D O I
10.1109/TSC.2016.2637929
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing applications must be allocated sufficient resources to comply with Service Level Agreements (SLAs). This paper considers data-driven probabilistic modeling of application resource demand for resource allocation. The modeling method is focused on peak demand and SLA violations and relies on a branch of statistics known as extreme value theory (EVT). Rigorous statistical validation of the proposed model shows that it generalizes better than the alternative. The paper presents a resource allocation algorithm using the model to ensure a given small SLA violation rate. For resource allocation in Yahoo data center, over 50 percent savings are demonstrated using the proposed approach.
引用
收藏
页码:987 / 993
页数:7
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