Multiway Reliability Analysis of Mobile Broadband Networks

Abstract

Understanding and characterizing the reliability of a mobile broadband network is a challenging task due to the presence of a multitude of root causes that operate at different temporal and spatial scales. This, in turn, limits the use of classical statistical methods for characterizing the mobile network's reliability. We propose leveraging tensor factorizations, a well-established data mining method, to address this challenge. We represent a year-long time series of outages, from two mobile operators as multi-way arrays, and demonstrate how tensor factorizations help in extracting the outage patterns at various time-scales, making it easy to locate possible root causes. Unlike traditional methods of time series analysis, tensor factorizations provide a compact and interpretable picture of outages.