Data-Driven Techniques in Computing System Management

Author:

Li Tao1ORCID,Zeng Chunqiu2,Jiang Yexi2,Zhou Wubai2,Tang Liang2,Liu Zheng3,Huang Yue3

Affiliation:

1. Nanjing University of Posts and Telecommunications 8 Florida International University, Miami, FL, USA

2. Florida International University, Miami, FL, USA

3. Nanjing University of Posts and Telecommunications, Nanjing, China

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.

Funder

Ministry of Education/China Mobile joint research

Scientific and Technological Support Project (Society) of Jiangsu

FIU Dissertation Year Fellowship

Chinese National Natural Science Foundation

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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