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A Mechanism of Telecommunication Network Performance Monitoring Based on Anomaly Detection |
Yu Yan-hua; Song Jun-de |
The School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing 1000876, China |
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Abstract With operation and maintenance mode of telecommunication network changing from ‘network oriented’ to ‘subscriber oriented’, network performance management should also be changed from passive monitoring to proactive monitoring. Proactive Performance Monitoring (PPM) enables a fast fault correction by detecting anomalies designating performance degradation. In this paper, a novel anomaly detection approach is proposed taking advantage of time series prediction and associated confidence interval based on Support Vector Machines (SVM). In addition a novel meta-parameters selection approach is proposed by checking if the training residual is white noise. Theoretical analysis and experimental results verify the correctness of the meta-parameter selection approach and the effectiveness of anomaly detection mechanism.
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Received: 22 September 2008
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