Detection on network equipment failure using Naïve bayes classification

Network downtime is one of the most widely shared phenomenon within the telecommunications infrastructure. In particular, faults from network equipment have received the most attention. Proactive network monitoring system is presented in this paper to address the earliest symptoms of malfunctioning network equipment. Research focus has been placed on learning the network’s behavior as well as on detecting deviations from the MSAN (Multi-Service Access Node) norm at the access layer. Additionally, this paper aims to provide an overview in handling the MSAN equipment, warnings, and implementation of Naïve Bayes classifier. Results demonstrated the throughput performance associated with the equipment activities log