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An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps
Joint Authors
Liu, Jun
Chen, Shuyu
Zhou, Zhen
Wu, Tianshu
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Virtual machines (VM) on a Cloud platform can be influenced by a variety of factors which can lead to decreased performance and downtime, affecting the reliability of the Cloud platform.
Traditional anomaly detection algorithms and strategies for Cloud platforms have some flaws in their accuracy of detection, detection speed, and adaptability.
In this paper, a dynamic and adaptive anomaly detection algorithm based on Self-Organizing Maps (SOM) for virtual machines is proposed.
A unified modeling method based on SOM to detect the machine performance within the detection region is presented, which avoids the cost of modeling a single virtual machine and enhances the detection speed and reliability of large-scale virtual machines in Cloud platform.
The important parameters that affect the modeling speed are optimized in the SOM process to significantly improve the accuracy of the SOM modeling and therefore the anomaly detection accuracy of the virtual machine.
American Psychological Association (APA)
Liu, Jun& Chen, Shuyu& Zhou, Zhen& Wu, Tianshu. 2016. An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112045
Modern Language Association (MLA)
Liu, Jun…[et al.]. An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps. Mathematical Problems in Engineering No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1112045
American Medical Association (AMA)
Liu, Jun& Chen, Shuyu& Zhou, Zhen& Wu, Tianshu. An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112045
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112045