Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)

An Event Modeling and Analysis Method Based on Bipartite Graph

Authors
Mei Xu, Yanlei Shang
Corresponding Author
Mei Xu
Available Online September 2016.
DOI
https://doi.org/10.2991/iccia-16.2016.25How to use a DOI?
Keywords
Event Modeling; Vertex-centric Algorithm; Bipartitie Graph; Event Analysis.
Abstract
As information systems become larger and more complex, maintenance and failure recovery become more difficult. Usually, these information systems monitor system state and business logic by logs or events. Analyzing these events which contain vital information in-depth is very necessary for both business intelligence, trouble shooting and event mining. There are several excellent event analysis methods including Complex Event Processing (CEP) which focus on processing complex events composed of single events. However, CEP cannot compute the relationship between events easily. In this paper, we propose a method for modeling events using Bipartite Graph. Besides, we achieve a vertex-centric algorithm that can be executed parallel to analyze the relationship between events or event sources. After that, we prove the feasibility and validity of the modeling method and algorithm with a sample experiment.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
Part of series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-240-4
ISSN
2352-538X
DOI
https://doi.org/10.2991/iccia-16.2016.25How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Mei Xu
AU  - Yanlei Shang
PY  - 2016/09
DA  - 2016/09
TI  - An Event Modeling and Analysis Method Based on Bipartite Graph
BT  - 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
PB  - Atlantis Press
SP  - 130
EP  - 140
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-16.2016.25
DO  - https://doi.org/10.2991/iccia-16.2016.25
ID  - Xu2016/09
ER  -