Capacity Analysis-Based Topology Planning and Traffic Scheduling for Time-Sensitive Networking

With the ability to provide deterministic transmission, time sensitive networking (TSN) has been widely used in various industrial scenarios. However, most of the existing TSN research focuses on traffic scheduling over predefined network topology. In industrial applications, optimizing network topology can reduce the number of network devices and the length of cables thereby lowering material and management costs, yet considering topology within TSN scheduling greatly increases the problem’s complexity. In this article, we first incorporate topology planning and traffic scheduling together into the TSN network design problem (TDP). A mathematical model for TDP is formulated, with the objective of minimizing the total weight and cost of a TSN network while satisfying the end-to-end deterministic transmission requirements. Subsequently, we establish the metric of capacity of TSN flow groups (CoG), and the proposed CoG estimation method enables feasibility assessment of TDP solutions. Since CoG measures a network’s capacity to accommodate TSN flows, we utilize it as the evaluation metric within our heuristic algorithm, CoG analysis based TSN network design algorithm (CATDA), reducing ineffective searches and enhancing the solution efficiency of TDP. Experiments show that compared to other algorithms, the proposed CATDA achieves the lowest-cost TSN network design solution and performs over 100 times faster than other algorithms.