With real-time communication being a key part of the fourth industrial revolution, the need for Quality of Service (QoS) in industrial networks is gaining increasing importance. Time-Sensitive Networking (TSN) faces this need, for example, by introducing new scheduling mechanisms. The Credit-Based Shaper (CBS) has been introduced to TSN to offer low delays for multiple traffic classes by applying rate limitations. Currently, flows are reserved decentrally in CBS networks using a Stream Reservation Protocol (SRP). In contrast, the new TSN standard IEEE 802.1Qcc allows for a centralized architecture to favor short reconfiguration latencies. However, no online admission control scheme which offers safe delay bounds has been proposed for this central architecture. To close this gap, we propose two models for admission control in TSN networks using CBS. Both models offer deadline-guaranteeing flow allocation, including routing and prioritization of flows, and configure forwarding devices while eliminating packet loss. Our models utilize the mathematical framework of Network Calculus to calculate worst-case flow delays and buffer sizes. We show how our models allow for more reservations than the decentralized standard approach by improved resource utilization. We validate our models both in synthetic and industrial network scenarios. Additionally, we compare the effects and parameters of our two models, providing guidance on when to choose them.
Resource reservation is a fundamental mechanism for ensuring quality of service in time-sensitive networks, which can be decentralized by using reservation protocols. In the Ethernet technology Time-Sensitive Networking, this has been proposed in conjunction with the Credit-Based Shaper. For the reservation, the standards assume a maximum worstcase latency bound at each hop. However, we will show through formal analysis and simulation that these worstcase latency bounds are not safe. To face this, we propose an extension to the current standards to allow the reservation of time-sensitive traffic with reliable latency guarantees. The effectiveness of our approach is demonstrated through simulations of both synthetic and industrial networks. Finally, by providing additional information about neighboring devices, we could further increase the maximum reservable traffic by up to 20% in our test cases.
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