Abstract

Various Industrial Internet of Things (IIoT) devices and their compelling applications have witnessed exponential growth over the past few years. Compared to the consumer internet, the industrial IoT often faces tough communication latency boundaries and low packet loss. Recently, time-sensitive networks (TSN) technique has been considered the most promising solution to tackle these issues, providing deterministic communication guarantees for time-sensitive applications. In TSN, to achieve bounded low latency, it introduces the Cyclic Queuing and Forwarding (CQF) mechanism to shape and regulate the transmission selection to provide the protected transmission window for time-triggered (TT) flows. Currently, a considerable amount of literature has explored traffic scheduling with the CQF mechanism in TSN. However, these methods ignore the impact of routing policy on scheduling optimization. In this paper, we design two algorithms to tackle the problem of joint routing and scheduling optimization with the CQF mechanism for TSN. We propose a TT flow sorting algorithm (JDPS) to measure the scheduling priority weight of each TT flow, which uses the normalization method to calculate the weight based on the flow's deadline, period, and size. Then, we propose a joint routing and scheduling optimization with load balance algorithm (JRS-LB) to improve the scheduling success radio and the network resource utilization, which jointly considers the injection time slot offset, scheduling, and routing of TT traffic. The evaluation results mainly focus on the scheduling success ratio, execution time, and resource utilization for the proposed algorithm compared to the Tabu and Naive algorithms. Extensive simulations indicate that the proposed JDPS and JRS-LB algorithms can improve the scheduling success radio compared with the other algorithms.

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