Critical event prediction for proactive management in large-scale computer clusters
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
First Course On Fuzzy Theory And Applications.
First Course On Fuzzy Theory And Applications.
A causal mapping approach to constructing Bayesian networks
Decision Support Systems
Proactive Self-Healing System based on Multi-Agent Technologies
SERA '05 Proceedings of the Third ACIS Int'l Conference on Software Engineering Research, Management and Applications
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Distributed computing systems are continuously increasing in complexity and cost of managing, and system management tasks require significantly higher levels of autonomic management. In distributed computing, system management is changing from a conventional central administration, to autonomic computing. However, most existing research focuses on healing after a problem has already occurred. In order to solve this problem, an inference model is required to recognize operating environments and predict error occurrence. In this paper, we proposed a hybrid inference model – ID3, Fuzzy Logic, FNN and Bayesian Network – through four algorithms supporting self-healing in autonomic computing. This inference model adopts a selective healing model, according to system situations for self-diagnosing and prediction of problems using four algorithms. Therefore, correction of error prediction becomes possible. In this paper, a hybrid inference model is adopted to evaluate the proposed model in a self-healing system. In addition, inference is compared with existing research and the effectiveness is demonstrated by experiment.