RG QoE is generally interested in topics relevant to QoE. Everyone is invited to participate in the topic area. Among others, RG QoE is currently investigating the following three topics in detail in the area of Quality of Experience
  1. QoE Fairness and Benchmarking Metrics,
  2. Crowdsourcing-based Performance Benchmarking,
  3. Benchmarking of Music Streaming Towards Quality of Experience.
QoE Fairness deals with the case of joint assessment of multiple users and applications in a common scenario. QoE is used here as a comparison metric. The aim is to be able to weigh different user ratings and experiences across application boundaries. The QoE should reflect a value that represents the satisfaction equally for multiple different applications. An example are applications running in a cloud system that share the cloud host's resources. With QoE fairness, it can be evaluated which application works better than the other running applications. This results in system-independent measured values that are based solely on the experience and satisfaction of the users of the applications. With this, a system configuration can be changed to balance the satisfaction of all users of applications in the cloud system. Under certain circumstances, this can also be an unfair allocation of resources, which then, in turn, results in a fair QoE for all users. This is because applications need different resources to deliver good or acceptable QoE to their users. This interest group deals with all topics related to the term QoE fairness and welcomes interested parties.
Contact: Tobias Hoßfeld, Crowdsourcing-based Performance Benchmarking deals with the case of massive user ratings for a system or infrastructure. This group is currently, but not exclusively, dealing with the evaluation of mobile communication systems, which is currently being heavily researched in the community. An Internet service provider uses an app or end-user measurements to survey the situation of the mobile communication network from the user's perspective. As a result, the users submit many individual, differently measured values for the mobile communication system. The challenge then lies in obtaining a generally valid and reliable rating about the overall performance of the system. For example, if there are more user ratings in a city than in the countryside, then the ratings in the city should not be overestimated when considering the overall performance. Furthermore, a statement or guideline must also be discussed and defined to what extent one can estimate whether an evaluation with a certain number of individual ratings allows a representative benchmarking. The temporal and spatial resolution of the individual ratings play a major role here. Above all, in other domains, such as big data, these questions are also important. We hope to work together in this field with other RG groups, companies and scientists. Contact: Florian Wamser, Music Streaming takes into account the current trend of listening to songs, audio books and playlists. It is closely linked to video streaming, but differs in the areas of resource consumption and usage behavior. Video streaming consumes more resources due to the larger content. Music Streaming, in contrast, is used commonly for longer time and also in the background. For many users, it is developing into an everyday background activity that is primarily intended to work continuously in every place. Further on, the usage behavior is different, as music streaming is often used while on the go, in the car or on the train. It has the advantage for the user that it can be used on all devices; even on devices with no or limited screen, such as smart speakers or smartphones. The RG QoE would like to examine QoE-related metrics for music streaming in order to be able to quantify how well a user is currently experiencing music streaming. For all three areas we are looking for interested parties who are willing to work on these topics. Contact: Anika Schwind,