On the Assessment and Debugging of QoE in SDN (Work in Progress)

被引:0
|
作者
Reyes, Jose [1 ]
Lopez, Jorge [1 ]
Kushik, Natalia [1 ]
Zeghlache, Djamal [1 ]
机构
[1] Telecom SudParis, SAMOVAR, CNRS, Inst Polytech Paris, Evry, France
关键词
Quality of Experience; Software Defined Networking; Machine Learning; Debugging; /; Diagnosis;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paper presents a work in progress on the Quality of Experience (QoE) assessment in the context of Software Defined Networking (SDN). Preliminary experimental results clearly demonstrate the necessity of considering QoE parameters, which are not taken into account in traditional networks. Dynamic network (re-) configuration requires monitoring and measuring attributes not only at the network level but also at the control and application planes. We discuss a list of such parameters and propose a monitoring algorithm to consider distributed and asynchronous points of observation for the QoE assessment of SDN network services. Further, for the cases when a low QoE level is detected (or predicted using machine learning), we propose an algorithm for effective diagnosis of the QoE degradation, based on an iterative deduction of a QoE attribute contributing the most to a low QoE value.
引用
收藏
页码:29 / 31
页数:3
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