Evolution of storage management: Transforming raw data into information

被引：9

作者：

Gopisetty, S. ^{[1
]}

Agarwala, S. ^{[1
]}

Butler, E. ^{[1
]}

Jadav, D. ^{[1
]}

Jaquet, S. ^{[1
]}

Korupolu, M. ^{[1
]}

Routray, R. ^{[1
]}

Sarkar, P. ^{[1
]}

Singh, A. ^{[1
]}

Sivan-Zimet, M. ^{[1
]}

Tan, C. -H. ^{[1
]}

Uttamchandani, S. ^{[1
]}

Merbach, D. ^{[2
]}

Padbidri, S. ^{[1
]}

Dieberger, A. ^{[1
]}

Haber, E. M. ^{[1
]}

Kandogan, E. ^{[1
]}

Kieliszewski, C. A. ^{[1
]}

Agrawal, D. ^{[3
]}

Devarakonda, M. ^{[4
]}

Lee, K. -W. ^{[3
]}

Magoutis, K. ^{[4
]}

Verma, D. C. ^{[3
]}

Vogl, N. G. ^{[4
]}

机构：

[1] IBM Almaden Res Ctr, San Jose, CA 95120 USA

[2] IBM Corp, Syst & Technol Grp, Rochester, MN 55901 USA

[3] IBM Res Div, Thomas J Watson Res Ctr, Hawthorne, NY 10532 USA

[4] IBM Corp, Div Res, Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA

来源：

IBM JOURNAL OF RESEARCH AND DEVELOPMENT | 2008年 / 52卷 / 4-5期

关键词：

D O I：

10.1147/rd.524.0341

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Exponential growth in storage requirements and an increasing number of heterogeneous devices and application policies are making enterprise storage management a nightmare for administrators. Back-of-the-envelope calculations, rules of thumb, and manual correlation of individual device data are too error prone for the day-to-day administrative tasks of resource provisioning, problem determination, performance management, and impact analysis. Storage management tools have evolved over the past several years from standardizing the data reported by storage subsystems to providing intelligent planners. In this paper, we describe that evolution in the context of the IBM TotalStorage (R) Productivity Center (TPC)-a suite of tools to assist administrators in the day-to-day tasks of monitoring, configuring, provisioning, managing change, analyzing configuration, managing performance, and determining problems. We describe our ongoing research to develop ways to simplify and automate these tasks by applying advanced analytics on the performance statistics and raw configuration and event data collected by TPC using the popular Storage Management Initiative-Specification (SMI-S). In addition, we provide details of SMART (storage management analytics and reasoning technology) as a library that provides a collection of data-aggregation functions and optimization algorithms.

引用

页码：341 / 352

页数：12

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