IJEEDC Fault Classification and Forecasting Using AI in Backbone Networks

Journal Paper

Paper Title :Fault Classification and Forecasting Using AI in Backbone Networks

Author :Gaurav Kumar, Aditya Vaidya, Abhimanyu Singh

Article Citation :Gaurav Kumar ,Aditya Vaidya ,Abhimanyu Singh , (2024 ) " Fault Classification and Forecasting Using AI in Backbone Networks " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 15-26, Volume-12,Issue-7

Abstract : Unintentional disruptions of Backbone network services, or network failures, cause annoyance to the end service user. This is particularly true for time sensitive services which subsequently result in huge losses. Additionally, there is a growing tendency toward remote working via a dependable network since physical working has become more expensive for businesses worldwide, therefore having a stable network connection is essential. Additionally, network failure costs Backbone Service Providers huge amounts in terms of revenue every year, negatively affecting their ability to operate. For Backbone networks to function flawlessly and without delay, a failure classification and forecasting mechanism is needed to proactively generate alarms for minimising loss of data and revenue. Keywords - Network Failure, Network Failure Detection, Network Availability, AI for Network Faults, Fault Classification and Fault Forecasting

Type : Research paper

Published : Volume-12,Issue-7


	\|		PDF	\|	Viewed - 21	\|	Published on 2024-10-15

Jan. 2025
Submitted Papers	:	80
Accepted Papers	:	10
Rejected Papers	:	70
Acc. Perc	:	12%
Issue Published	:	141
Paper Published	:	1771
No. of Authors	:	4924

Published : Volume-12,Issue-7

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