Betreuer/in: Baron
Time-Sensitive Networking (TSN) coordinates Ethernet transmissions to provide
deterministic communication, whereas a 5G configured grant exposes capacity
only during recurring transmission occasions.
This thesis investigates how a TSN
scheduler can represent that periodic resource and when its recurring occasions permit admission of a periodic stream. The proposed model describes a configured grant by its period, phase, and
occasion length and applies it as an availability mask to the segment-based Time-
Aware Shaper (TAS) scheduler of the Incremental Task and Network Scheduling
(ITANS) framework. An analytical alignment condition uses the circular spread of
stream-instance phases to test whether one period-relative offset places every instance
inside an occasion. The analysis distinguishes the finite interval represented by the
scheduler from asymptotic repetition, while the evaluation model adds deterministic
5G bridge residence before downstream TAS forwarding. Controlled experiments show that comparable airtime does not imply comparable admission because temporal alignment determines which stream classes can use a grant. The finite-schedule condition separates zero-admission from nonzeroadmission cases in the evaluated data, but capacity and incremental packing still determine how many structurally feasible streams fit. Absolute grant phase also affects admission in the evaluated multi-hop fixture. The result is a feasibility filter and design guideline for future joint 5G–TSN resource selection, not a complete radio-resource scheduler. The quantitative scope covers one shared grant pattern on one configured-grant-masked port of the ordinary greatest-common-divisor-based stream scheduling path (STREAM–GCD) and does not constitute a physical 5G measurement. On this path, admission does not consult a stream deadline; deadline compliance is checked only after admission.
Room 04.137, Martensstr. 3, Erlangen
or
Zoom:
https://fau.zoom-x.de/j/68350702053?pwd=UkF3aXY0QUdjeSsyR0tyRWtLQ0hYUT09
Meeting-ID: 683 5070 2053
Kenncode: 647333