@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{HossfeldHeegaardKellerer2023,
  author    = {Hossfeld, Tobias and Heegaard, Poul E. and Kellerer, Wolfgang},
  title     = {Comparing the scalability of communication networks and systems},
  series = {IEEE Access},
  volume    = {11},
  journal   = {IEEE Access},
  doi       = {10.1109/ACCESS.2023.3314201},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-349403},
  pages     = {101474-101497},
  year      = {2023},
  abstract  = {Scalability is often mentioned in literature, but a stringent definition is missing. In particular, there is no general scalability assessment which clearly indicates whether a system scales or not or whether a system scales better than another. The key contribution of this article is the definition of a scalability index (SI) which quantifies if a system scales in comparison to another system, a hypothetical system, e.g., linear system, or the theoretically optimal system. The suggested SI generalizes different metrics from literature, which are specialized cases of our SI. The primary target of our scalability framework is, however, benchmarking of two systems, which does not require any reference system. The SI is demonstrated and evaluated for different use cases, that are (1) the performance of an IoT load balancer depending on the system load, (2) the availability of a communication system depending on the size and structure of the network, (3) scalability comparison of different location selection mechanisms in fog computing with respect to delays and energy consumption; (4) comparison of time-sensitive networking (TSN) mechanisms in terms of efficiency and utilization. Finally, we discuss how to use and how not to use the SI and give recommendations and guidelines in practice. To the best of our knowledge, this is the first work which provides a general SI for the comparison and benchmarking of systems, which is the primary target of our scalability analysis.},
  language  = {en}
}