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Performance Evaluation Methodologies and Tools. 16th EAI International Conference, VALUETOOLS 2023, Crete, Greece, September 6–7, 2023, Proceedings

Research Article

Combining Static and Dynamic Traffic with Delay Guarantees in Time-Sensitive Networking

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-48885-6_8,
        author={Lisa Maile and Kai-Steffen Hielscher and Reinhard German},
        title={Combining Static and Dynamic Traffic with Delay Guarantees in Time-Sensitive Networking},
        proceedings={Performance Evaluation Methodologies and Tools. 16th EAI International Conference, VALUETOOLS 2023, Crete, Greece, September 6--7, 2023, Proceedings},
        proceedings_a={VALUETOOLS},
        year={2024},
        month={1},
        keywords={Performance modeling Network optimization Latency guarantees Auto-configuration Resource allocation Time-sensitive networking},
        doi={10.1007/978-3-031-48885-6_8}
    }
    
  • Lisa Maile
    Kai-Steffen Hielscher
    Reinhard German
    Year: 2024
    Combining Static and Dynamic Traffic with Delay Guarantees in Time-Sensitive Networking
    VALUETOOLS
    Springer
    DOI: 10.1007/978-3-031-48885-6_8
Lisa Maile1,*, Kai-Steffen Hielscher1, Reinhard German1
  • 1: Computer Networks and Communication Systems
*Contact email: lisa.maile@fau.de

Abstract

To support reliable and low-latency communication, Time-Sensitive Networking introduced protocols and interfaces for resource allocation in Ethernet. However, the implementation of these allocation algorithms has not yet been covered by the standards. Our work focuses on deadline-guaranteeing resource allocation for networks with static and dynamic traffic. To achieve this, we combine offline network optimization heuristics with online admission control and, thus, allow for new flow registrations while the network is running. We demonstrate our solution on Credit-Based Shaper networks by using the delay analysis framework Network Calculus. We compare our approach with an intuitive and a brute-force algorithm, where we can achieve significant improvements, both, in terms of quality and runtime. Thereby, our results show that we can guarantee maximum end-to-end delays and also increase the flexibility of the network while requiring only minimal user input.

Keywords
Performance modeling Network optimization Latency guarantees Auto-configuration Resource allocation Time-sensitive networking
Published
2024-01-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-48885-6_8
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