Automated Anomaly and Root Cause Detection in Distributed Systems
Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2012, Vol 3, Issue 1
Abstract
It is a challenging issue to identify a defective system in a large scale network. The data collected from the distributed systems for troubleshooting is very huge and may contain noisy data, so manual checking and detecting of the abnormal node is time consuming and error prone. In order to solve this, we need to develop an automated system that detects the anomaly. Though the defective node is found it has to be rectified, for this we need to know the root cause of the problem. In this paper we present an automated mechanism for node level anomaly detection in large-scale systems and the root cause for anomaly. A set of data mining techniques are used here to analyze the collected data and to identify the nodes acting differently from others. We use Independent Component Analysis (ICA) for feature extraction. We also present some of the mechanisms needed to know the root cause of the problem. So the results will be abnormal nodes and problem to be rectified in them. These can be validated manually
Authors and Affiliations
G. D. K. Kishore1 , Maddali Sravanthi2 , Kurma Siva Naga Mrudhula3 , J Sandeep4 , Kilaru Swapna5
Keywords
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