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DNet Publications

2020

  • Fabien Geyer and Steffen Bondorf. Graph-based Deep Learning for Fast and Tight Network Calculus Analyses. In IEEE Transactions on Network Science and Engineering (@IEEE, bib)
  • Steffen Bondorf and Fabien Geyer. Virtual Cross-Flow Detouring in the Deterministic Network Calculus Analysis. In Proc. of IFIP Networking (@IFIP, @IEEE, bib)
  • Bruno Cattelan, Steffen Bondorf and Alberto E. Schaeffer-Filho. An Empirical Study of Tightest Network Calculus Analyses for Networks with Multicast Flows. In Proc. of IEEE COMPSAC (@IEEE, bib)
  • Bruno Cattelan and Steffen Bondorf. On Delay Bounds and Measurements: A COTS Testbed for Network Performance Experimentation. In Proc. of IEEE ADMNET (IEEE COMPSAC Workshops) (@IEEE, bib)
  • Fabien Geyer and Steffen Bondorf. On the Robustness of Deep Learning-predicted Contention Models for Network Calculus. In Proc. of IEEE ISCC (@IEEE, @ArXiv, bib)

2019

  • Fabien Geyer and Steffen Bondorf. On the Robustness of Deep Learning-predicted Contention Models for Network Calculus. arXiv:1911.10522v1 [cs.NI], 24 Nov 2019. (@ArXiv, bib)