dc.contributor.author | Hossfeld, Tobias | |
dc.contributor.author | Heegaard, Poul Einar | |
dc.contributor.author | Skorin-Kapov, Lea | |
dc.contributor.author | Varela, Martin | |
dc.contributor.author | Fiedler, Markus | |
dc.date.accessioned | 2021-02-04T13:57:10Z | |
dc.date.available | 2021-02-04T13:57:10Z | |
dc.date.created | 2020-12-11T08:50:45Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-1-7281-5685-9 | |
dc.identifier.uri | https://hdl.handle.net/11250/2726234 | |
dc.description.abstract | In the context of QoE management, network and service providers commonly rely on models that map system QoS conditions (e.g., system response time, paket loss, etc.) to estimated end user QoE values. Observable QoS conditions in the system may be assumed to follow a certain distribution, meaning that different end users will experience different conditions. On the other hand, drawing from the results of subjective user studies, we know that user diversity leads to distributions of user scores for any given test conditions (in this case referring to the QoS parameters of interest). Our previous studies have shown that to correctly derive various QoE metrics (e.g., Mean Opinion Score (MOS), quantiles, probability of users rating “good or better”, etc.) in a system under given conditions, there is a need to consider rating distributions obtained from user studies, which are often times not available. In this paper we extend these findings to show how to approximate user rating distributions given a QoS-to-MOS mapping function and second order statistics. Such a user rating distribution may then be combined with a QoS distribution observed in a system to finally derive corresponding distributions of QoE scores. We provide two examples to illustrate this process: 1) analytical results using a Web QoE model relating waiting times to QoE, and 2) numerical results using measurements relating packet losses to video stall pattern, which are in turn mapped to QoE estimates. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.ispartof | Proceedings of the 2020 IEEE Conference on Network Softwarization | |
dc.title | From QoS Distributions to QoE Distributions: a System's Perspective | en_US |
dc.type | Chapter | en_US |
dc.description.version | acceptedVersion | en_US |
dc.source.pagenumber | 51-56 | en_US |
dc.identifier.doi | 10.1109/NetSoft48620.2020.9165426 | |
dc.identifier.cristin | 1858569 | |
dc.description.localcode | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |