LUCAS - an expert system for intelligent fault management and alarm correlation

Author(s):  
H.-J. Kettschau ◽  
S. Bruck ◽  
P. Schefczik
Author(s):  
Philippe Fournier-Viger ◽  
Ganghuan He ◽  
Min Zhou ◽  
Mourad Nouioua ◽  
Jiahong Liu

Author(s):  
Jyoti Shetty ◽  
Sathish Babu B. ◽  
Shobha G.

Cloud resiliency is an important issue in successful implementation of cloud computing systems. Handling cloud faults proactively, with a suitable remediation technique having minimum cost is an important requirement for a fault management system. The selection of best applicable remediation technique is a decision making problem and considers parameters such as i) Impact of remediation technique ii) Overhead of remediation technique ii) Severity of fault and iv) Priority of the application. This manuscript proposes an analytical model to measure the effectiveness of a remediation technique for various categories of faults, further it demonstrates the implementation of an efficient fault remediation system using a rule-based expert system. The expert system is designed to compute an utility value for each remediation technique in a novel way and select the best remediation technique from its knowledgebase. A prototype is developed for experimentation purpose and the results shows improved availability with less overhead as compared to a reactive fault management system.


2020 ◽  
Vol 53 (2) ◽  
pp. 10485-10492
Author(s):  
M.A. Benatia ◽  
A. Louis ◽  
D. Baudry

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