Analysis and classification of network device alarm clusters
Giovanni Genna
Analysis and classification of network device alarm clusters.
Rel. Paolo Garza, Luca Colomba. Politecnico di Torino, Master of science program in Computer Engineering, 2024
Abstract
The application of machine learning and data mining has seen a rise over the past decade thanks to their recent success in different fields, ranging from computer vision, biomedical data analyses to natural language processing. The field of computer networks and network maintenance has also observed the application of such concepts. This thesis is a result of an ongoing collaboration with TIM SpA. Overall, the studies presented in this manuscript consist in the analysis of the alarms raised by TIM network devices both in mobile and transmission domains, with the ultimate goal of developing a real-time environment that can help technicians to quickly determine faults within their network and solve them faster.
The first step of the thesis consists in studying the results obtained by an already existing clustering and data mining algorithms, which were developed ad-hoc in a previous study.The clustering algorithm groups alarms raised in similar space-time contexts and identifies critical events within the system
Publication type
URI
 |
Modify record (reserved for operators) |
