Comparing Statistical and Analytical Routing Approaches for Delay-Tolerant Networks

Pedro R. D'Argenio, Juan A. Fraire, Arnd Hartmanns*, Fernando D. Raverta

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
56 Downloads (Pure)


In delay-tolerant networks (DTNs) with uncertain contact plans, the communication episodes and their reliabilities are known a priori. To maximize the end-to-end delivery probability, a bounded network-wide number of message copies are allowed. The resulting multi-copy routing optimization problem is naturally modelled as a Markov decision process with distributed information. The two state-of-the-art solution approaches are statistical model checking with scheduler sampling, and the analytical RUCoP algorithm based on probabilistic model checking. In this paper, we provide an in-depth comparison of the two approaches. We use an extensive benchmark set comprising random networks, scalable binomial topologies, and realistic ring-road low Earth orbit satellite networks. We evaluate the obtained message delivery probabilities as well as the computational effort. Our results show that both approaches are suitable tools for obtaining reliable routes in DTN, and expose a trade-off between scalability and solution quality.
Original languageEnglish
Title of host publicationQuantitative Evaluation of Systems
Subtitle of host publication19th International Conference, QEST 2022, Warsaw, Poland, September 12–16, 2022, Proceedings
EditorsErika Ábrahám, Marco Paolieri
Number of pages19
ISBN (Electronic)978-3-031-16336-4
ISBN (Print)978-3-031-16335-7
Publication statusPublished - 11 Sept 2022
Event19th International Conference on Quantitative Evaluation of Systems, QEST 2022 - Warsaw, Poland
Duration: 12 Sept 202216 Sept 2022
Conference number: 19

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Quantitative Evaluation of Systems, QEST 2022
Abbreviated titleQEST


  • This work was part of the MISSION (Models in Space Systems: Integration, Operation, and Networking) project, funded by the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie Actions grant number 101008233.
  • 2023 OA procedure


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