Deriving QoE in systems: from fundamental relationships to a QoE-based Service-level Quality Index
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RESEARCH ARTICLE
Deriving QoE in systems: from fundamental relationships to a QoE‑based Service‑level Quality Index Tobias Hoßfeld1 · Poul E. Heegaard2 · Lea Skorin‑Kapov3 · Martín Varela4 Received: 29 November 2019 © The Author(s) 2020
Abstract With Quality of Experience (QoE) research having made significant advances over the years, service and network providers aim at user-centric evaluation of the services provided in their system. The question arises how to derive QoE in systems. In the context of subjective user studies conducted to derive relationships between influence factors and QoE, user diversity leads to varying distributions of user rating scores for different test conditions. Such models are commonly exploited by providers to derive various QoE metrics in their system, such as expected QoE, or the percentage of users rating above a certain threshold. The question then becomes how to combine (a) user rating distributions obtained from subjective studies, and (b) system parameter distributions, so as to obtain the actual observed QoE distribution in the system? Moreover, how can various QoE metrics of interest in the system be derived? We prove fundamental relationships for the derivation of QoE in systems, thus providing an important link between the QoE community and the systems community. In our numerical examples, we focus mainly on QoE metrics. We furthermore provide a more generalized view on quantifying the quality of systems by defining a QoE-based Service-level Quality Index. This index exploits the fact that quality can be seen as a proxy measure for utility. Following the assumption that not all user sessions should be weighted equally, we aim to provide a generic framework that can be utilized to quantify the overall utility of a service delivered by a system. Keywords QoE fundamentals · Expected QoE · Expected MOS · Good-or-Better (GoB) · QoS-QoE mapping functions · Service-level Quality Index (SQI)
Introduction One of the main research challenges faced by the the QoE community is deriving QoE models for various applications and services, whereby ratings collected from subjective user * Tobias Hoßfeld tobias.hossfeld@uni‑wuerzburg.de Poul E. Heegaard [email protected] Lea Skorin‑Kapov lea.skorin‑[email protected] Martín Varela [email protected] 1
University of Würzburg, Chair of Communication Networks, Würzburg, Germany
2
NTNU - Norwegian University of Science and Technology, Department of Information Security and Communication Technology, Trondheim, Norway
3
University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia
4
Profilence, Oulu, Finland
studies are used to model the relationship between tested influence factors and QoE. With it being well known that different users perceive both quality and value differently [1], user diversity will inherently impact the distribution of rating scores for a given test condition [2, 3]. However, the majority of user studies to-date still report only on MOS (Mean Opinion Score) values and confidence int
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