@techreport{BlenkKellererHossfeld2020,
  type      = {Working Paper},
  author    = {Blenk, Andreas and Kellerer, Wolfgang and Hoßfeld, Tobias},
  title     = {Technical Report on DFG Project SDN-App: SDN-enabled Application-aware Network Control Architectures and their Performance Assessment},
  doi       = {10.25972/OPUS-20755},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207558},
  year      = {2020},
  abstract  = {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 W{\"u}rzburg. The project started at the institutions in Munich and W{\"u}rzburg 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.},
  subject      = {Software-defined networking},
  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}
}