A Machine Learning-Based Framework to Estimate the Lifetime of Network Line Cards

被引：3
|
作者：
Herrera, Juan Luis [1 ]
Polverini, Marco [2 ]
Galan-Jimenez, Jaime [1 ]
机构：
[1] Univ Extremadura, Dept Comp Syst & Telemat Engn, Badajoz, Spain
[2] Univ Rome Sapienza, DIET Dept, Rome, Italy
来源：
NOMS 2020 - PROCEEDINGS OF THE 2020 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2020: MANAGEMENT IN THE AGE OF SOFTWARIZATION AND ARTIFICIAL INTELLIGENCE | 2020年
关键词：
Machine Learning; line card; lifetime; estimation; QoS;
D O I：
10.1109/noms47738.2020.9110455
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
With the increasing tendency on data rates in forthcoming communication networks, availability is a crucial aspect to guarantee Quality of Service (QoS) requirements. The possibility of predicting the lifetime of networking hardware can be a key to improve the overall network QoS. This paper proposes a generic Machine Learning (ML) based framework that learns how to mimic the mathematical model behind the lifetime of network line cards. Results show that a good precision (85%) and recall (close to 100%) on the estimation can be achieved regardless the type of line cards the network is composed of.
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页数：5
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