Publications Conference paper · Delay-tolerant networks · 2022

Comparing Statistical and Analytical Routing Approaches for Delay-Tolerant Networks

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

International Conference on Quantitative Evaluation of Systems (QEST), vol. 13479, pp. 337–355, 2022

Abstract

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 networkwide 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.

Cite

DOI 10.1007/978-3-031-16336-4_17

BibTeX

@inproceedings{DBLP:conf/qest/DArgenioFHR22,
  author    = {Pedro R. D'Argenio and Juan A. Fraire and Arnd Hartmanns and Fernando D. Raverta},
  editor    = {Erika {\'{A}}brah{\'{a}}m and Marco Paolieri},
  title     = {Comparing Statistical and Analytical Routing Approaches for Delay-Tolerant Networks},
  booktitle = {International Conference on Quantitative Evaluation of Systems (QEST)},
  series    = {Lecture Notes in Computer Science},
  volume    = {13479},
  pages     = {337--355},
  publisher = {Springer},
  year      = {2022},
  doi       = {10.1007/978-3-031-16336-4_17}
}

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