TY - JOUR A1 - Hoßfeld, Tobias A1 - Heegaard, Poul E. A1 - Skrorin-Kapov, Lea A1 - Varela, Martín T1 - Deriving QoE in systems: from fundamental relationships to a QoE-based Service-level Quality Index JF - Quality and User Experience N2 - 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. KW - QoE fundamentals KW - Expected QoE KW - Expected MOS KW - Good-or-Better (GoB) KW - QoS-QoE mapping functions KW - Service-level Quality Index (SQI) Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-235597 SN - 2366-0139 VL - 5 ER - TY - JOUR A1 - Borchert, Kathrin A1 - Seufert, Anika A1 - Gamboa, Edwin A1 - Hirth, Matthias A1 - Hoßfeld, Tobias T1 - In Vitro vs In Vivo: Does the Study's Interface Design Influence Crowdsourced Video QoE? JF - Quality and User Experience N2 - Evaluating the Quality of Experience (QoE) of video streaming and its influence factors has become paramount for streaming providers, as they want to maintain high satisfaction for their customers. In this context, crowdsourced user studies became a valuable tool to evaluate different factors which can affect the perceived user experience on a large scale. In general, most of these crowdsourcing studies either use, what we refer to, as an in vivo or an in vitro interface design. In vivo design means that the study participant has to rate the QoE of a video that is embedded in an application similar to a real streaming service, e.g., YouTube or Netflix. In vitro design refers to a setting, in which the video stream is separated from a specific service and thus, the video plays on a plain background. Although these interface designs vary widely, the results are often compared and generalized. In this work, we use a crowdsourcing study to investigate the influence of three interface design alternatives, an in vitro and two in vivo designs with different levels of interactiveness, on the perceived video QoE. Contrary to our expectations, the results indicate that there is no significant influence of the study’s interface design in general on the video experience. Furthermore, we found that the in vivo design does not reduce the test takers’ attentiveness. However, we observed that participants who interacted with the test interface reported a higher video QoE than other groups. KW - video QoE KW - crowdsourcing KW - study design KW - user study KW - distraction Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-235586 SN - 2366-0139 VL - 6 ER - TY - RPRT A1 - Blenk, Andreas A1 - Kellerer, Wolfgang A1 - Hoßfeld, Tobias T1 - Technical Report on DFG Project SDN-App: SDN-enabled Application-aware Network Control Architectures and their Performance Assessment N2 - The DFG project “SDN-enabled Application-aware Network Control Architectures and their Performance Assessment” (DFG SDN-App) focused in phase 1 (Jan 2017 – Dec 2019) on software defined networking (SDN). Being a fundamental paradigm shift, SDN enables a remote control of networking devices made by different vendors from a logically centralized controller. In principle, this enables a more dynamic and flexible management of network resources compared to the traditional legacy networks. Phase 1 focused on multimedia applications and their users’ Quality of Experience (QoE). This documents reports the achievements of the first phase (Jan 2017 – Dec 2019), which is jointly carried out by the Technical University of Munich, Technical University of Berlin, and University of Würzburg. The project started at the institutions in Munich and Würzburg in January 2017 and lasted until December 2019. In Phase 1, the project targeted the development of fundamental control mechanisms for network-aware application control and application-aware network control in Software Defined Networks (SDN) so to enhance the user perceived quality (QoE). The idea is to leverage the QoE from multiple applications as control input parameter for application-and network control mechanisms. These mechanisms are implemented by an Application Control Plane (ACP) and a Network Control Plane (NCP). In order to obtain a global view of the current system state, applications and network parameters are monitored and communicated to the respective control plane interface. Network and application information and their demands are exchanged between the control planes so to derive appropriate control actions. To this end, a methodology is developed to assess the application performance and in particular the QoE. This requires an appropriate QoE modeling of the applications considered in the project as well as metrics like QoE fairness to be utilized within QoE management. In summary, the application-network interaction can improve the QoE for multi-application scenarios. This is ensured by utilizing information from the application layer, which are mapped by appropriate QoS-QoE models to QoE within a network control plane. On the other hand, network information is monitored and communicated to the application control plane. Network and application information and their demands are exchanged between the control planes so to derive appropriate control actions. KW - Software-defined networking KW - Quality of Experience KW - SDN KW - QoE Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-207558 ER - TY - RPRT A1 - Grigorjew, Alexej A1 - Metzger, Florian A1 - Hoßfeld, Tobias A1 - Specht, Johannes A1 - Götz, Franz-Josef A1 - Schmitt, Jürgen A1 - Chen, Feng T1 - Technical Report on Bridge-Local Guaranteed Latency with Strict Priority Scheduling N2 - Bridge-local latency computation is often regarded with caution, as historic efforts with the Credit-Based Shaper (CBS) showed that CBS requires network wide information for tight bounds. Recently, new shaping mechanisms and timed gates were applied to achieve such guarantees nonetheless, but they require support for these new mechanisms in the forwarding devices. This document presents a per-hop latency bound for individual streams in a class-based network that applies the IEEE 802.1Q strict priority transmission selection algorithm. It is based on self-pacing talkers and uses the accumulated latency fields during the reservation process to provide upper bounds with bridge-local information. The presented delay bound is proven mathematically and then evaluated with respect to its accuracy. It indicates the required information that must be provided for admission control, e.g., implemented by a resource reservation protocol such as IEEE 802.1Qdd. Further, it hints at potential improvements regarding new mechanisms and higher accuracy given more information. KW - Echtzeit KW - Rechnernetz KW - Latenz KW - Ethernet KW - Latency Bound KW - Formal analysis Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-198310 ER - TY - RPRT A1 - Grigorjew, Alexej A1 - Metzger, Florian A1 - Hoßfeld, Tobias A1 - Specht, Johannes A1 - Götz, Franz-Josef A1 - Chen, Feng A1 - Schmitt, Jürgen T1 - Asynchronous Traffic Shaping with Jitter Control N2 - Asynchronous Traffic Shaping enabled bounded latency with low complexity for time sensitive networking without the need for time synchronization. However, its main focus is the guaranteed maximum delay. Jitter-sensitive applications may still be forced towards synchronization. This work proposes traffic damping to reduce end-to-end delay jitter. It discusses its application and shows that both the prerequisites and the guaranteed delay of traffic damping and ATS are very similar. Finally, it presents a brief evaluation of delay jitter in an example topology by means of a simulation and worst case estimation. KW - Echtzeit KW - Rechnernetz KW - Latenz KW - Ethernet KW - TSN KW - jitter KW - traffic damping Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-205824 ER -