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Steffen Bondorf
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Publications
- 2023
- [j7]Fabien Geyer, Alexander Scheffler, Steffen Bondorf:
Network Calculus With Flow Prolongation - A Feedforward FIFO Analysis Enabled by ML. IEEE Trans. Computers 72(1): 97-110 (2023) - [i6]Fabien Geyer, Steffen Bondorf:
Differentiable Programming & Network Calculus: Configuration Synthesis under Delay Constraints. CoRR abs/2307.14280 (2023) - 2022
- [c25]Fabien Geyer, Steffen Bondorf:
Network Synthesis under Delay Constraints: The Power of Network Calculus Differentiability. INFOCOM 2022: 1539-1548 - [i5]Fabien Geyer, Alexander Scheffler, Steffen Bondorf:
Network Calculus with Flow Prolongation - A Feedforward FIFO Analysis enabled by ML. CoRR abs/2202.03004 (2022) - 2021
- [j4]Fabien Geyer, Steffen Bondorf:
Graph-Based Deep Learning for Fast and Tight Network Calculus Analyses. IEEE Trans. Netw. Sci. Eng. 8(1): 75-88 (2021) - [c20]Fabien Geyer, Alexander Scheffler, Steffen Bondorf:
Tightening Network Calculus Delay Bounds by Predicting Flow Prolongations in the FIFO Analysis. RTAS 2021: 157-170 - 2020
- [c17]Fabien Geyer, Steffen Bondorf:
On the Robustness of Deep Learning-predicted Contention Models for Network Calculus. ISCC 2020: 1-7 - [c16]Steffen Bondorf, Fabien Geyer:
Virtual Cross-Flow Detouring in the Deterministic Network Calculus Analysis. Networking 2020: 554-558 - 2019
- [c15]Fabien Geyer, Steffen Bondorf:
DeepTMA: Predicting Effective Contention Models for Network Calculus using Graph Neural Networks. INFOCOM 2019: 1009-1017 - [p1]Steffen Bondorf, Fabien Geyer:
Deterministic Network Calculus Analysis of Multicast Flows. Systems Modeling: Methodologies and Tools 2019: 63-78 - [i3]Fabien Geyer, Steffen Bondorf:
On the Robustness of Deep Learning-predicted Contention Models for Network Calculus. CoRR abs/1911.10522 (2019) - 2016
- [c5]Steffen Bondorf, Fabien Geyer:
Generalizing Network Calculus Analysis to Derive Performance Guarantees for Multicast Flows. VALUETOOLS 2016
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