Regulation de traffic dans les réseaux temps réel large-échelle et multi-domaines

Offre de thèse

Date limite de candidature

01-08-2026

Date de début de contrat

01-10-2026

Directeur de thèse

SONG Ye Qiong

Encadrement

This PhD position is in the context of FRONTIER project as part of PEPR Future Networks. The PhD student will be co-supervised with regular bi-monthly meetings. In parallel with his PhD work, he will follow the training program of IAEM doctoral school. The progress will also be followed by the CSI committee with annual meetings.

Type de contrat

Financement d'un établissement public Français

Candidater à cette offre

école doctorale

IAEM - INFORMATIQUE - AUTOMATIQUE - ELECTRONIQUE - ELECTROTECHNIQUE - MATHEMATIQUES

équipe

SIMBIOT

contexte

The PhD takes place in the context of the FRONTIER research project (part of the PEPR Future Networks https://pepr-futurenetworks.fr/). FRONTIER aims at enabling largescale time-sensitive networks for the control of large-scale cyber-physical systems such as smart grids.

spécialité

Informatique

laboratoire

LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications

Mots clés

Time-Sensitive Networking (TSN), Deterministic Networking (DetNet), Traffic Shaping, Traffic Policing, Network Calculus

Détail de l'offre

Background:
Time-sensitive networks are used for safety-critical cyber-physical systems (CPSs) in
vehicles, planes, satellites or power plants. Their significance has been increasing over
the years and they are now used in many more applications, ranging from autonomous
cars, automated manufactures (industry 4.0) to 5G and beyond backbone networks. While
traditional public networks aim at improving the mean service performances (mean
round trip time, mean throughput), time-sensitive networks provide guarantees for the
worst case (e.g. guarantee of a maximal latency, guarantee of no loss, …). Time-sensitive
networks use specific layer-2 technologies from IEEE TSN [TSN] for providing
deterministic latency.
Among these technologies are traffic regulators such as Aynchronous Traffic Shaping.
Traffic regulators force the traffic to conform to a given specification, delaying the packets
if required. They are particularly useful as they remove the burst-cascade effect (the
burstiness of the flows tend to increase along their paths).
Time-sensitive networks control increasingly large and dynamic systems (smart-grid
systems, unmanned air traffic management, public transportation systems). In these
large-scale and often multi-actors networks, traffic regulators are required at each point
that crosses the frontier between two network domains. Yet, the traffic regulators
currently available do not scale to large-scale networks with a large number of different
flows.

Project description:
The goal of the PhD is to investigate, design and evaluate new traffic regulation
mechanisms that scale to a large number of flows and a large traffic rate and to be
deployed at the frontier of several network domains in a large-scale time-sensitive
network.
Among the possible research directions are:
– Investigate approaches for aggregating multiple flows into a compound flow,
where only the compound flow is regulated.
– Investigate new regulation techniques that do not require storing a per-flow state
in memory, possibly by having regulation data written in the packet's header,
implement them on an embedded system to check their scalability.
– Investigate the efficient and scalable configuration of traffic regulators in largescale
multi-domains networks.

Keywords

Time-Sensitive Networking (TSN), Deterministic Networking (DetNet), Traffic Shaping, Traffic Policing, Network Calculus

Subject details

Background: Time-sensitive networks are used for safety-critical cyber-physical systems (CPSs) in vehicles, planes, satellites or power plants. Their significance has been increasing over the years and they are now used in many more applications, ranging from autonomous cars, automated manufactures (industry 4.0) to 5G and beyond backbone networks. While traditional public networks aim at improving the mean service performances (mean round trip time, mean throughput), time-sensitive networks provide guarantees for the worst case (e.g. guarantee of a maximal latency, guarantee of no loss, …). Time-sensitive networks use specific layer-2 technologies from IEEE TSN [TSN] for providing deterministic latency. Among these technologies are traffic regulators such as Aynchronous Traffic Shaping. Traffic regulators force the traffic to conform to a given specification, delaying the packets if required. They are particularly useful as they remove the burst-cascade effect (the burstiness of the flows tend to increase along their paths). Time-sensitive networks control increasingly large and dynamic systems (smart-grid systems, unmanned air traffic management, public transportation systems). In these large-scale and often multi-actors networks, traffic regulators are required at each point that crosses the frontier between two network domains. Yet, the traffic regulators currently available do not scale to large-scale networks with a large number of different flows. Project description: The goal of the PhD is to investigate, design and evaluate new traffic regulation mechanisms that scale to a large number of flows and a large traffic rate and to be deployed at the frontier of several network domains in a large-scale time-sensitive network. Among the possible research directions are: – Investigate approaches for aggregating multiple flows into a compound flow, where only the compound flow is regulated. – Investigate new regulation techniques that do not require storing a per-flow state in memory, possibly by having regulation data written in the packet's header, implement them on an embedded system to check their scalability. – Investigate the efficient and scalable configuration of traffic regulators in largescale multi-domains networks.

Profil du candidat

· Very good programming skills.
· Knowledge of computer networks (layered approach, etc).
· Interest in time-sensitive systems is a plus.
· Knowledge on embedded systems is a plus.
· Knowledge on FGPA, VHDL, DPDK or P4 is a plus.

Candidate profile

Référence biblio

[TSN] “Time-Sensitive Networking (TSN) Task Group |.” Accessed: Nov. 06, 2022.
Available: https://1.ieee802.org/tsn/
[LeBoudec01] J.-Y. Le Boudec and P. Thiran, Network Calculus, vol. 2050. in Lecture Notes in Computer Science, vol. 2050. Berlin, Heidelberg: Springer, 2001. doi: 10.1007/3-540-45318-0.
[Geyer22] F. Geyer and S. Bondorf, “Network Synthesis under Delay Constraints: The Power of Network Calculus Differentiability,” in IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, May 2022, pp. 1539–1548. doi: 10.1109/INFOCOM48880.2022.9796777.
[Tsai24] C.-T. Tsai, S. M. Tabatabaee, S. Plassart, and J.-Y. Le Boudec, “Saihu: A common interface of worst-case delay analysis tools for time-sensitive networks,” SoftwareX, vol. 27, p. 101882, Sept. 2024, doi: 10.1016/j.softx.2024.101882.