Long-distance Deterministic Transmission among TSN Networks: Converging CQF and DIP

Abstract

With the development of 5G, innovative applications requiring bounded transmission delays and zero packet loss emerge, e.g., AR, industrial automation, and smart grid. In this circumstance, time-sensitive networking (TSN) is proposed, which addresses the deterministic transmission in the local area networks. Nevertheless, TSN is essentially a Layer 2 technique, which cannot provide deterministic transmission on a large geographic area. To solve this problem, this paper proposes a hierarchical network for the end-to-end deterministic transmission. In the proposed network, we leverage CQF (i.e., one of the most efficient TSN mechanisms) in the access networks which aggregates the traffic from end-devices. Meanwhile, in the core network, we exploit the DIP (i.e., a well-known deterministic networking mechanism for backbone networks) for long-distance deterministic transmission. We design the cycle alignment mechanism to enable seamless and deterministic transmission among hierarchical networks. A joint schedule is also formulated, which introduces the traffic shaping at the network edge to maximize the network throughput. Experimental simulations show that the proposed network can achieve end-to-end deterministic transmission, even in the highly-load scenarios.