@techreport{MetzgerSchroederRafetseder2021,
  type      = {Working Paper},
  author    = {Metzger, Florian and Schr{\"o}der, Svenja and Rafetseder, Albert},
  title     = {Subjective And Objective Assessment Of Video Game Context Factors},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242471},
  pages     = {7},
  year      = {2021},
  abstract  = {The recently published ITU-T Recommendation G1.032 proposes a list of factors that may influence cloud and online gaming Quality of Experience (QoE). This paper provides two practical evaluations of proposed system and context influence factors: First, it investigates through an online survey (n=488) the popularity of platforms, preferred ways of distribution, and motivational aspects including subjective valuations of characteristics offered by today's prevalent gaming platforms. Second, the paper evaluates a large dataset of objective metrics for various gaming platforms: game lists, playthrough lengths, prices, etc., and contrasts these metrics against the gamers' opinions. The combined data-driven approach presented in this paper complements in-person and lab studies usually employed.},
  subject      = {Videospiel},
  language  = {en}
}
@techreport{MetzgerRafetsederSchroederetal.2016,
  type      = {Working Paper},
  author    = {Metzger, Florian and Rafetseder, Albert and Schr{\"o}der, Svenja and Zwickl, Patrick},
  title     = {The Prospects of Cloud Gaming: Do the Benefits Outweigh the Costs?},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242452},
  pages     = {10},
  year      = {2016},
  abstract  = {In recent years, cloud gaming has become a popular research topic and has claimed many benefits in the commercial domain over conventional gaming. While, cloud gaming platforms have frequently failed in the past, they have received a new impetus over the last years that brought it to the edge of commercial breakthrough. The fragility of the cloud gaming market may be caused by the high investment costs, offered pricing models or competition from existing "{\`a} la carte" platforms. This paper aims at investigating the costs and benefits of both platform types through a twofold approach. We first take on the perspective of the customers, and investigate several cloud gaming platforms and their pricing models in comparison to the costs of other gaming platforms. Then, we explore engagement metrics in order to assess the enjoyment of playing the offered games. Lastly, coming from the perspective of the service providers, we aim to identify challenges in cost-effectively operating a large-scale cloud gaming service while maintaining high QoE values. Our analysis provides initial, yet still comprehensive reasons and models for the prospects of cloud gaming in a highly competitive market.},
  subject      = {Cloud Computing},
  language  = {en}
}
@techreport{Metzger2020,
  type      = {Working Paper},
  author    = {Metzger, Florian},
  title     = {Crowdsensed QoE for the community - a concept to make QoE assessment accessible},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203748},
  pages     = {7},
  year      = {2020},
  abstract  = {In recent years several community testbeds as well as participatory sensing platforms have successfully established themselves to provide open data to everyone interested. Each of them with a specific goal in mind, ranging from collecting radio coverage data up to environmental and radiation data. Such data can be used by the community in their decision making, whether to subscribe to a specific mobile phone service that provides good coverage in an area or in finding a sunny and warm region for the summer holidays. However, the existing platforms are usually limiting themselves to directly measurable network QoS. If such a crowdsourced data set provides more in-depth derived measures, this would enable an even better decision making. A community-driven crowdsensing platform that derives spatial application-layer user experience from resource-friendly bandwidth estimates would be such a case, video streaming services come to mind as a prime example. In this paper we present a concept for such a system based on an initial prototype that eases the collection of data necessary to determine mobile-specific QoE at large scale. In addition we reason why the simple quality metric proposed here can hold its own.},
  subject      = {Quality of Experience},
  language  = {en}
}