Research on proactive performance monitoring mechanism for mobile network

The mode of telecommunications network management is changing from ´network-centered´ to ´subscriber-centered´. Aimed to improve subscribers´ experience, proactive performance monitoring is elaborated to enable 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 multiplicative ARIMA. Furthermore, under the assumption that the training residual which is a white noise process follows normal distribution, the associated confidence interval of prediction can be figured out under any given confidence degree 1-a by constructing random variable satisfying t distribution. Experimental results verify the effectiveness of the approach.