Genetic Algorithm for Scheduling Time-Triggered Traffic in Time-Sensitive Networks

Abstract

Time-Sensitive Networking (TSN) is introduced as a series of Ethernet extensions to address strict temporal constraints of modern mission-critical applications. TSN offers determinism using global Time-Triggered (TT) transmission schedules. Most of existing scheduling solutions ignore interdependence of routing and scheduling problems and derive the design space of system implementations only from scheduling constraints. This strategy limits the capability of former approaches to compute a global schedule of TT communication for several real-time systems. In this paper, we present a heuristic scheduling approach based on a genetic algorithm. Our approach combines the routing and scheduling constraints and generates static global schedules using joint constraints in a single-step. The number of scheduling possibilities within the design space that is derived from joint routing and scheduling constraints increases in comparison to the approaches that only use the fixed routing. Thereby, the schedulability is improved by our solution. Our genetic-based approach also considers the distribution of real-time applications, multicast patterns and interdependencies of TT flows in the scheduling process. Due to optimized task binding and resource allocation, the experimental results show a significant enhancement of schedulability, TT transmission efficiency and resource utilization compared to the state-of-art solutions.