Online Updating in Multicast Time-Sensitive Networking

Jiachen Wen, Ying Wang, Qianqian Zhang, Jingjing Chen, Xuesong Qiu

Abstract: With the rapid increase of applications of the Industrial Internet of Things (IIoT), supporting the rapid update and deployment of Time-Sensitive Networking (TSN) in dynamic scenarios has become a major challenge. However, most proposals focus on implementing offline generation of scheduling tables in TSN based on time-aware shapers (TAS), and are not suitable for automation scenarios such as network redeployment under frequent changes in devices, especially in complex networks. In order to maximize the resource efficiency of timeslots and ensure load balance, while reducing bandwidth waste to accommodate more schedulable flows, we designed a heuristic online incremental update algorithm (OIU) compatible with the TAS mechanism to deploy multicast flows. The evaluation results indicate that compared with existing work, the OIU algorithm has improved its operational efficiency by at least 20 times in high load flow scenarios. At the same time, its support of multicast has also improved load balancing on the link.