Log Pattern Mining for Distributed System Maintenance
Joint Authors
Chen, Jia
Wang, Peng
Du, Shiqing
Wang, Wei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-01
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Due to the complexity of the network structure, log analysis is usually necessary for the maintenance of network-based distributed systems since logs record rich information about the system behaviors.
In recent years, numerous works have been proposed for log analysis; however, they ignore temporal relationships between logs.
In this paper, we target on the problem of mining informative patterns from temporal log data.
We propose an approach to discover sequential patterns from event sequences with temporal regularities.
Discovered patterns are useful for engineers to understand the behaviors of a network-based distributed system.
To solve the well-known problem of pattern explosion, we resort to the minimum description length (MDL) principle and take a step forward in summarizing the temporal relationships between adjacent events of a pattern.
Experiments on real log datasets prove the efficiency and effectiveness of our method.
American Psychological Association (APA)
Chen, Jia& Wang, Peng& Du, Shiqing& Wang, Wei. 2020. Log Pattern Mining for Distributed System Maintenance. Complexity،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1143071
Modern Language Association (MLA)
Chen, Jia…[et al.]. Log Pattern Mining for Distributed System Maintenance. Complexity No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1143071
American Medical Association (AMA)
Chen, Jia& Wang, Peng& Du, Shiqing& Wang, Wei. Log Pattern Mining for Distributed System Maintenance. Complexity. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1143071
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143071