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Data-Driven Techniques in Computing System Management

ACM Computing Surveys2017Vol. 50(3), pp. 1–43

Citations Over TimeTop 10% of 2017 papers

Tao Li, Chunqiu Zeng, Yexi Jiang, Wubai Zhou, Liang Tang, Zheng Liu, Yue Huang

Abstract

Modern forms of computing systems are becoming progressively more complex, with an increasing number of heterogeneous hardware and software components. As a result, it is quite challenging to manage these complex systems and meet the requirements in manageability, dependability, and performance that are demanded by enterprise customers. This survey presents a variety of data-driven techniques and applications with a focus on computing system management. In particular, the survey introduces intelligent methods for event generation that can transform diverse log data sources into structured events, reviews different types of event patterns and the corresponding event-mining techniques, and summarizes various event summarization methods and data-driven approaches for problem diagnosis in system management. We hope this survey will provide a good overview for data-driven techniques in computing system management.

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