Detection on network equipment failure using Naïve bayes classification

Citation

Tan, Yi Fei and Lai, Jie Yan and Lam, Hai Shuan and Xiaoning, Guo and Soo, Wooi King (2017) Detection on network equipment failure using Naïve bayes classification. In: 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), 15-17 Dec. 2017, Chengdu.

[img] Text
8.pdf - Published Version
Restricted to Repository staff only

Download (282kB)

Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Network equipment,machine learning,Naive Bayes,telecommunications network, equipment failure
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1-484 Motor vehicles. Cycles
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 27 Mar 2021 18:27
Last Modified: 27 Mar 2021 18:27
URII: http://shdl.mmu.edu.my/id/eprint/7545

Downloads

Downloads per month over past year

View ItemEdit (login required)