A Survey of Machine Learning for Network Fault Management

Telecommunication networks play a major role in today’s society as they support the transmission of information between businesses, governments, and individuals. Hence, ensuring excellent service quality and avoiding service disruptions are important. For this purpose, fault management is critical. It consists of detecting, isolating, and fixing network problems, a task that is complex for large networks, and typically requires considerable resources. As a result, an emerging research area is to develop machine learning and data mining-based techniques to improve various aspects of the fault management process. This chapter provides a survey of data mining and machine learning-based techniques for fault management, including a description of their characteristics, similarities, differences, and shortcomings.