NDLI: Cognitive behavior analysis framework for fault prediction in cloud computing

Content Provider	IEEE Xplore Digital Library
Author	Moghaddam, R.F. Moghaddam, F.F. Asghari, V. Cheriet, M.
Copyright Year	2012
Description	Author affiliation: INRS-EMT, University of Quebec, Montreal (QC), Canada H5A 1K6 (Asghari, V.) \|\| Synchromedia Lab, ETS, University of Quebec, Montreal (QC), Canada H3C 1K3 (Moghaddam, R.F.; Moghaddam, F.F.; Cheriet, M.)
Abstract	Complex computing systems, including clusters, grids, clouds and skies, are becoming the fundamental tools of green and sustainable ecosystems of future. However, they can also pose critical bottlenecks and ignite disasters. The complexity and high number of variables could easily go beyond the capacity of any analyst or traditional operational research paradigm. In this work, we introduce a multi-paradigm, multi-layer and multi-level behavior analysis framework which can adapt to the behavior of a target complex system. It not only learns and detects normal and abnormal behaviors, it could also suggest cognitive responses in order to increase the system resilience and its grade. The multi-paradigm nature of the framework provides a robust redundancy in order to cross-cover possible hidden aspects of each paradigm. After providing the high-level design of the framework, three different paradigms are discussed. We consider the following three paradigms: Probabilistic Behavior Analysis, Simulated Probabilistic Behavior Analysis, and Behavior-Time Profile Modeling and Analysis. To be more precise and because of paper limitations, we focus on the fault prediction in the paper as a specific event-based abnormal behavior. We consider both spontaneous and gradual failure events. The promising potential of the framework has been demonstrated using simple examples and topologies. The framework can provide an intelligent approach to balance between green and high probability of completion (or high probability of availability) aspects in computing systems.
Starting Page	1
Ending Page	8
File Size	1580946
Page Count	8
File Format	PDF
ISBN	9781467352635
e-ISBN	9781467352659
e-ISBN	9781467352642
DOI	10.1109/NOF.2012.6464008
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-21
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Availability Analytical models Barium Ecosystems Probabilistic logic Software Hardware
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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