Evaluation of Metaheuristic Algorithms for TAS Scheduling in Time-Sensitive Networking

Time Sensitive Networking (TSN) is an emerging technology for providing deterministic ultra low-latency network based on Ethernet. It is designed for application domains such as industrial automation where guaranteed latency is required to meet the hard deadlines of flows. TSN achieves this by carefully scheduling the transmissions of frames through the IEEE 802.1Qbv standard, also known as time-aware shaper (TAS). However, TAS scheduling problem is classified as NP-hard. To overcome this challenge, we explore various metaheuristic approaches using MEALPY, a state-of-the-art meta-heuristic algorithm module of Python. We evaluate the meta-heuristic algorithms for TAS scheduling optimization problem through TSN simulations and provide observations for future directions.