@techreport{VomhoffGeisslerHossfeld2022,
  type      = {Working Paper},
  author    = {Vomhoff, Viktoria and Geißler, Stefan and Hoßfeld, Tobias},
  title     = {Identification of Signaling Patterns in Mobile IoT Signaling Traffic},
  series = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)},
  journal   = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)},
  doi       = {10.25972/OPUS-28081},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280819},
  pages     = {4},
  year      = {2022},
  abstract  = {We attempt to identify sequences of signaling dialogs, to strengthen our understanding of the signaling behavior of IoT devices by examining a dataset containing over 270.000 distinct IoT devices whose signaling traffic has been observed over a 31-day period in a 2G network [4]. We propose a set of rules that allows the assembly of signaling dialogs into so-called sessions in order to identify common patterns and lay the foundation for future research in the areas of traffic modeling and anomaly detection.},
  subject      = {Datennetz},
  language  = {en}
}
@techreport{RaffeckGeisslerHossfeld2022,
  type      = {Working Paper},
  author    = {Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias},
  title     = {DBM: Decentralized Burst Mitigation for Self-Organizing LoRa Deployments},
  series = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)},
  journal   = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)},
  doi       = {10.25972/OPUS-28080},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280809},
  pages     = {4},
  year      = {2022},
  abstract  = {This work proposes a novel approach to disperse dense transmission intervals and reduce bursty traffic patterns without the need for centralized control. Furthermore, by keeping the mechanism as close to the Long Range Wide Area Network (LoRaWAN) standard as possible the suggested mechanism can be deployed within existing networks and can even be co-deployed with other devices.},
  subject      = {Datennetz},
  language  = {en}
}
@techreport{GrigorjewDiederichHossfeldetal.2022,
  type      = {Working Paper},
  author    = {Grigorjew, Alexej and Diederich, Philip and Hoßfeld, Tobias and Kellerer, Wolfgang},
  title     = {Affordable Measurement Setups for Networking Device Latency with Sub-Microsecond Accuracy},
  series = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)},
  journal   = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)},
  doi       = {10.25972/OPUS-28075},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280751},
  pages     = {5},
  year      = {2022},
  abstract  = {This document presents a networking latency measurement setup that focuses on affordability and universal applicability, and can provide sub-microsecond accuracy. It explains the prerequisites, hardware choices, and considerations to respect during measurement. In addition, it discusses the necessity for exhaustive latency measurements when dealing with high availability and low latency requirements. Preliminary results show that the accuracy is within ±0.02 μs when used with the Intel I350-T2 network adapter.},
  subject      = {Datennetz},
  language  = {en}
}
@article{LohPoigneeWamseretal.2021,
  author    = {Loh, Frank and Poign{\´e}e, Fabian and Wamser, Florian and Leidinger, Ferdinand and Hoßfeld, Tobias},
  title     = {Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming},
  series = {Sensors},
  volume    = {21},
  journal   = {Sensors},
  number    = {12},
  issn      = {1424-8220},
  doi       = {10.3390/s21124172},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-241121},
  year      = {2021},
  abstract  = {Streaming video is responsible for the bulk of Internet traffic these days. For this reason, Internet providers and network operators try to make predictions and assessments about the streaming quality for an end user. Current monitoring solutions are based on a variety of different machine learning approaches. The challenge for providers and operators nowadays is that existing approaches require large amounts of data. In this work, the most relevant quality of experience metrics, i.e., the initial playback delay, the video streaming quality, video quality changes, and video rebuffering events, are examined using a voluminous data set of more than 13,000 YouTube video streaming runs that were collected with the native YouTube mobile app. Three Machine Learning models are developed and compared to estimate playback behavior based on uplink request information. The main focus has been on developing a lightweight approach using as few features and as little data as possible, while maintaining state-of-the-art performance.},
  language  = {en}
}
@book{TranGiaHossfeld2021,
  author    = {Tran-Gia, Phuoc and Hoßfeld, Tobias},
  title     = {Performance Modeling and Analysis of Communication Networks},
  edition   = {1st edition},
  publisher = {W{\"u}rzburg University Press},
  address   = {W{\"u}rzburg},
  isbn      = {978-3-95826-152-5},
  doi       = {10.25972/WUP-978-3-95826-153-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-241920},
  publisher      = {W{\"u}rzburg University Press},
  pages     = {xiii, 353},
  year      = {2021},
  abstract  = {This textbook provides an introduction to common methods of performance modeling and analysis of communication systems. These methods form the basis of traffic engineering, teletraffic theory, and analytical system dimensioning. The fundamentals of probability theory, stochastic processes, Markov processes, and embedded Markov chains are presented. Basic queueing models are described with applications in communication networks. Advanced methods are presented that have been frequently used in recent practice, especially discrete-time analysis algorithms, or which go beyond classical performance measures such as Quality of Experience or energy efficiency. Recent examples of modern communication networks include Software Defined Networking and the Internet of Things. Throughout the book, illustrative examples are used to provide practical experience in performance modeling and analysis. Target group: The book is aimed at students and scientists in computer science and technical computer science, operations research, electrical engineering and economics.},
  language  = {en}
}
@article{HossfeldHeegaardSkrorinKapovetal.2020,
  author    = {Hoßfeld, Tobias and Heegaard, Poul E. and Skrorin-Kapov, Lea and Varela, Mart{\´i}n},
  title     = {Deriving QoE in systems: from fundamental relationships to a QoE-based Service-level Quality Index},
  series = {Quality and User Experience},
  volume    = {5},
  journal   = {Quality and User Experience},
  issn      = {2366-0139},
  doi       = {10.1007/s41233-020-00035-0},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235597},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@article{BorchertSeufertGamboaetal.2020,
  author    = {Borchert, Kathrin and Seufert, Anika and Gamboa, Edwin and Hirth, Matthias and Hoßfeld, Tobias},
  title     = {In Vitro vs In Vivo: Does the Study's Interface Design Influence Crowdsourced Video QoE?},
  series = {Quality and User Experience},
  volume    = {6},
  journal   = {Quality and User Experience},
  issn      = {2366-0139},
  doi       = {10.1007/s41233-020-00041-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235586},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@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{GrigorjewMetzgerHossfeldetal.2020,
  author    = {Grigorjew, Alexej and Metzger, Florian and Hoßfeld, Tobias and Specht, Johannes and G{\"o}tz, Franz-Josef and Chen, Feng and Schmitt, J{\"u}rgen},
  title     = {Asynchronous Traffic Shaping with Jitter Control},
  doi       = {10.25972/OPUS-20582},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-205824},
  pages     = {8},
  year      = {2020},
  abstract  = {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.},
  subject      = {Echtzeit},
  language  = {en}
}
@techreport{GrigorjewMetzgerHossfeldetal.2020,
  author    = {Grigorjew, Alexej and Metzger, Florian and Hoßfeld, Tobias and Specht, Johannes and G{\"o}tz, Franz-Josef and Schmitt, J{\"u}rgen and Chen, Feng},
  title     = {Technical Report on Bridge-Local Guaranteed Latency with Strict Priority Scheduling},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-198310},
  year      = {2020},
  abstract  = {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.},
  subject      = {Echtzeit},
  language  = {en}
}