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In-network Quality of Experience Monitoring of HTTP Adaptive Streaming Services (CROSBI ID 685093)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Oršolić, Irena ; Skorin-Kapov, Lea In-network Quality of Experience Monitoring of HTTP Adaptive Streaming Services // Proceedings of the International Conference on Smart Systems and Technologies 2018 (SST 2018). 2018. str. 1-2

Podaci o odgovornosti

Oršolić, Irena ; Skorin-Kapov, Lea

engleski

In-network Quality of Experience Monitoring of HTTP Adaptive Streaming Services

Due to the increasing adoption of encryption in Over-the-Top services, Internet Service Providers (ISPs) generally lack insight into service performance. Thus, to be able to detect Quality of Experience (QoE) degradations that could potentially be mitigated in the network, ISPs are looking for ways to infer QoE and Key Performance Indicators (KPIs) from statistical properties of network traffic. Research on this topic, including our work, has found machine learning techniques to give promising results for training models that map network-level parameters to QoE/KPIs. While a lot of efforts are currently being put into tackling this challenge, a number of open issues remain. The aim of this research is to further explore the possibilities of this approach and specify a framework that automates the model training process in a service- and platform-independent way, enabling extensive model (re)training and analysis.

QoE monitoring ; encrypted traffic ; YouTube ; machine learning

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Podaci o prilogu

1-2.

2018.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the International Conference on Smart Systems and Technologies 2018 (SST 2018)

Podaci o skupu

International Conference on Smart Systems and Technologies 2018(SST 2018)

poster

10.10.2018-12.10.2018

Osijek, Hrvatska

Povezanost rada

Računarstvo