Detection on network equipment failure using Naïve bayes classification

Tan Yi Fei; Lai Jie Yan; Lam Hai Shuan; Guo Xiaoning; Soo Wooi King

doi:10.1109/ITNEC.2017.8284990

Detection on network equipment failure using Naïve bayes classification

Tan Yi Fei, Lai Jie Yan, Lam Hai Shuan, Guo Xiaoning, Soo Wooi King

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017
Editors	Bing Xu
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	286-290
Number of pages	5
ISBN (Electronic)	9781509064137
DOIs	https://doi.org/10.1109/ITNEC.2017.8284990
Publication status	Published - 2 Jul 2017
Externally published	Yes
Event	IEEE Information Technology, Networking, Electronic and Automation Control Conference 2017 - Chengdu, China Duration: 15 Dec 2017 → 17 Dec 2017 Conference number: 2nd https://ieeexplore.ieee.org/xpl/conhome/8272884/proceeding (Proceedings)

Publication series

Name	Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017
Volume	2018-January

Conference

Conference	IEEE Information Technology, Networking, Electronic and Automation Control Conference 2017
Abbreviated title	ITNEC 2017
Country/Territory	China
City	Chengdu
Period	15/12/17 → 17/12/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8272884/proceeding (Proceedings)

Keywords

machine learning
Naive Bayes
telecommunications network equipment failure

Access to Document

10.1109/ITNEC.2017.8284990

Cite this

Fei, T. Y., Yan, L. J., Shuan, L. H., Xiaoning, G., & King, S. W. (2017). Detection on network equipment failure using Naïve bayes classification. In B. Xu (Ed.), Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017 (pp. 286-290). (Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017; Vol. 2018-January). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ITNEC.2017.8284990

Fei, Tan Yi ; Yan, Lai Jie ; Shuan, Lam Hai et al. / Detection on network equipment failure using Naïve bayes classification. Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017. editor / Bing Xu. IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 286-290 (Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017).

@inproceedings{0c0afa51cd764824b34f646a5227af5b,

title = "Detection on network equipment failure using Na{\"i}ve bayes classification",

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 Na{\"i}ve Bayes classifier. Results demonstrated the throughput performance associated with the equipment activities log.",

keywords = "machine learning, Naive Bayes, telecommunications network equipment failure",

author = "Fei, {Tan Yi} and Yan, {Lai Jie} and Shuan, {Lam Hai} and Guo Xiaoning and King, {Soo Wooi}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; IEEE Information Technology, Networking, Electronic and Automation Control Conference 2017, ITNEC 2017 ; Conference date: 15-12-2017 Through 17-12-2017",

year = "2017",

month = jul,

day = "2",

doi = "10.1109/ITNEC.2017.8284990",

language = "English",

series = "Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "286--290",

editor = "Bing Xu",

booktitle = "Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/8272884/proceeding",

}

Fei, TY, Yan, LJ, Shuan, LH, Xiaoning, G & King, SW 2017, Detection on network equipment failure using Naïve bayes classification. in B Xu (ed.), Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017. Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017, vol. 2018-January, IEEE, Institute of Electrical and Electronics Engineers, pp. 286-290, IEEE Information Technology, Networking, Electronic and Automation Control Conference 2017, Chengdu, China, 15/12/17. https://doi.org/10.1109/ITNEC.2017.8284990

Detection on network equipment failure using Naïve bayes classification. / Fei, Tan Yi; Yan, Lai Jie; Shuan, Lam Hai et al.
Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017. ed. / Bing Xu. IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 286-290 (Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Detection on network equipment failure using Naïve bayes classification

AU - Fei, Tan Yi

AU - Yan, Lai Jie

AU - Shuan, Lam Hai

AU - Xiaoning, Guo

AU - King, Soo Wooi

N1 - Conference code: 2nd

PY - 2017/7/2

Y1 - 2017/7/2

N2 - 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.

AB - 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.

KW - machine learning

KW - Naive Bayes

KW - telecommunications network equipment failure

UR - http://www.scopus.com/inward/record.url?scp=85046698603&partnerID=8YFLogxK

U2 - 10.1109/ITNEC.2017.8284990

DO - 10.1109/ITNEC.2017.8284990

M3 - Conference Paper

AN - SCOPUS:85046698603

T3 - Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017

SP - 286

EP - 290

BT - Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017

A2 - Xu, Bing

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE Information Technology, Networking, Electronic and Automation Control Conference 2017

Y2 - 15 December 2017 through 17 December 2017

ER -

Fei TY, Yan LJ, Shuan LH, Xiaoning G, King SW. Detection on network equipment failure using Naïve bayes classification. In Xu B, editor, Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017. IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 286-290. (Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017). doi: 10.1109/ITNEC.2017.8284990

Detection on network equipment failure using Naïve bayes classification

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Cite this