Correlating real-time monitoring data for mobile network management

With a proliferation of new mobile data services, the complexity of wireless mobile networks is rapidly growing. While large amount of operational monitoring data such as performance measurement statistics is available, it is a great challenge to correlate such data effectively for real time performance analysis. Meantime, the dynamics of mobile applications and environments introduce another dimension of complexity for us to track the evolving system status. In this paper, we analyze the spatial and temporal correlations of Key Performance Indicators (KPIs) to track and interpret the operational status of wide-area cellular systems. We first correlate large number of raw measurements into limited number of KPIs. Further we exploit spatial and temporal correlations of these KPIs for cellular network management. We use large volume of field data collected from real cellular systems in our analysis. Experimental results demonstrate that it is promising to build a real-time data management and support system by effectively correlating KPIs.