Log Pattern Mining for Distributed System Maintenance
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6628165 |
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| _version_ | 1832550826701225984 |
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| author | Jia Chen Peng Wang Shiqing Du Wei Wang |
| author_facet | Jia Chen Peng Wang Shiqing Du Wei Wang |
| author_sort | Jia Chen |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-41d287ac5d0047b2bbc3f17231d39cca |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-41d287ac5d0047b2bbc3f17231d39cca2025-02-03T06:05:40ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/66281656628165Log Pattern Mining for Distributed System MaintenanceJia Chen0Peng Wang1Shiqing Du2Wei Wang3School of Computer Science, Fudan University, Shanghai 200082, ChinaSchool of Computer Science, Fudan University, Shanghai 200082, ChinaSchool of Computer Science, Fudan University, Shanghai 200082, ChinaSchool of Computer Science, Fudan University, Shanghai 200082, ChinaDue 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.http://dx.doi.org/10.1155/2020/6628165 |
| spellingShingle | Jia Chen Peng Wang Shiqing Du Wei Wang Log Pattern Mining for Distributed System Maintenance Complexity |
| title | Log Pattern Mining for Distributed System Maintenance |
| title_full | Log Pattern Mining for Distributed System Maintenance |
| title_fullStr | Log Pattern Mining for Distributed System Maintenance |
| title_full_unstemmed | Log Pattern Mining for Distributed System Maintenance |
| title_short | Log Pattern Mining for Distributed System Maintenance |
| title_sort | log pattern mining for distributed system maintenance |
| url | http://dx.doi.org/10.1155/2020/6628165 |
| work_keys_str_mv | AT jiachen logpatternminingfordistributedsystemmaintenance AT pengwang logpatternminingfordistributedsystemmaintenance AT shiqingdu logpatternminingfordistributedsystemmaintenance AT weiwang logpatternminingfordistributedsystemmaintenance |