Efficient Task-Network Scheduling With Task Conflict Metric in Time-Sensitive Networking
Lei Xu, Qimin Xu, Cailian Chen, Yanzhou Zhang, Shouliang Wang, Xinping Guan
Abstract
With the rapid development of Industrial Internet of Things (IIoT), time-sensitive networking (TSN) with deterministic and real-time features has gained broad interest. However, most existing research focuses on the network scheduling with fixed task placement and computing resource allocation, restricting the scheduling space of coupled task-network. To tackle this coupling problem, an efficient task-network scheduling (ETNS) scheme is proposed in this article for TSN. A task-conflict metric (TCM) is established to quantify the competition degree of scheduling resources. For increasing the overall scheduling space, a TCM-aware prescheduling method is proposed by optimizing task placement and routing paths to reduce the potential conflicts between tasks. Integrated with the prescheduling method, we design a TCM-aware parallel group-scheduling algorithm by reducing the conflicts between task groups to enhance schedulability and scalability. Experiments show that our ETNS scheme significantly improves the schedulability and scalability performances compared with the existing scheduling approaches. The larger the number of tasks, the higher the performance improvement.