Characterizing and predicting resource demand by periodicity mining

被引：7

作者：

Andrzejak A. ^{[1
]}

Ceyran M. ^{[1
]}

机构：

[1] Zuse Institute Berlin (ZIB), 14195 Berlin-Dahlem

来源：

Journal of Network and Systems Management | 2005年 / 13卷 / 2期

关键词：

Pattern mining; Prediction; Resource management; Self-management;

D O I：

10.1007/s10922-005-4440-y

中图分类号：

学科分类号：

摘要：

We present algorithms for characterizing the demand behavior of applications and predicting demand by mining periodicities in historical data. Our algorithms are change-adaptive, automatically adjusting to new regularities in demand patterns while maintaining low algorithm running time. They are intended for applications in scientific computing clusters, enterprise data centers, and Grid and Utility environments that exhibit periodical behavior and may benefit significantly from automation. A case study incorporating data from an enterprise data center is used to evaluate the effectiveness of our technique. © 2005 Springer Science + Business Media, Inc.

引用

页码：175 / 196

页数：21

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