Call Availability Prediction in a Telecommunication System: A Data Driven Empirical Approach

Availability prediction in a telecommunication system plays a crucial role in its management, either by alerting the operator to potential failures or by proactively initiating preventive measures. In this paper, we apply linear (ARMA, multivariate, random walk) and nonlinear (Radial and Universal Basis Functions) regression techniques to recognize system failures and to predict the system's call availability up to 15 minutes in advance. Secondly we introduce a novel nonlinear modeling technique for call availability prediction. We benchmark all five techniques against each other. The applied modeling methods are data driven rather than analytical and can handle large amounts of data. We apply the modeling techniques to real data of a commercial telecommunication platform. The data used for modeling includes a) time stamped event-based log files and b) continuously measured system states. Results are given in terms of a) receiver operator characteristics (AUC) for classification ...

• Type: Conference
• Year: 2006
• Where: SRDS
• Authors: Günther A. Hoffmann, Miroslaw Malek
• Keywords: Availability Prediction, Modeling Technique, Nonlinear Modeling Techniques, SRDS 2006