Time-Sensitive Networking (TSN) is an enhancement of Ethernet which provides various mechanisms for real-time communication. Time-triggered (TT) traffic represents periodic data streams with strict real-time requirements. Amongst others, TSN supports scheduled transmission of TT streams, i.e., the transmission of their frames by end stations is coordinated in such a way that none or very little queuing delay occurs in intermediate nodes. TSN supports multiple priority queues per egress port. The TAS uses so-called gates to explicitly allow and block these queues for transmission on a short periodic timescale. The TAS is utilized to protect scheduled traffic from other traffic to minimize its queuing delay. In this work, we consider scheduling in TSN which comprises the computation of periodic transmission instants at end stations and the periodic opening and closing of queue gates. In this paper, we first give a brief overview of TSN features and standards. We state the TSN scheduling problem and explain common extensions which also include optimization problems. We review scheduling and optimization methods that have been used in this context. Then, the contribution of currently available research work is surveyed. We extract and compile optimization objectives, solved problem instances, and evaluation results. Research domains are identified, and specific contributions are analyzed. Finally, we discuss potential research directions and open problems.

Traditional IP multicast (IPMC) maintains state per IPMC group in core devices to distribute one-to-many traffic along tree-like structures through the network. This limits its scalability because whenever subscribers of IPMC groups change, forwarding state in the core network needs to be updated. Bit Index Explicit Replication (BIER) has been proposed by the IETF for efficient transport of IPMC traffic without the need of IPMC-group-dependent state in core devices. However, legacy devices do not offer the required features to implement BIER. P4 is a programming language which follows the software-defined networking (SDN) paradigm. It provides a programmable data plane by programming the packet processing pipeline of P4 devices. The contribution of this article is threefold. First, we provide a hardware-based prototype of BIER and BIER fast reroute (BIER-FRR) which leverages packet recirculation. Our target is the P4-programmable high-performance switching ASIC Tofino; the source code is publicly available. Second, we perform an experimental evaluation, with regard to failover time and throughput, which shows that up to 100 Gb/s throughput can be obtained and that failures affect BIER forwarding for less than 1 ms. However, throughput can decrease if switch-internal packet loss occurs due to missing recirculation capacity. As a remedy, we add more recirculation capacity by turning physical ports into loopback mode. To quantify the problem, we derive a prediction model for reduced throughput whose results are in good accordance with measured values. Third, we provide a provisioning rule for recirculation ports, that is applicable to general P4 programs, to avoid switch-internal packet loss due to packet recirculation. In a case study we show that BIER requires only a few such ports under realistic mixes of unicast and multicast traffic.

In this work, we present P4TG, a P4-based traffic generator (TG) which runs on the programmable Intel Tofino™ ASIC. In generation mode, P4TG is capable of generating traffic up to 1 Tb/s split across 10x 100 Gb/s ports. Thereby it measures rates directly in the data plane. Generated traffic may be fed back from the output to the input ports, possibly through other equipment, to record packet loss, packet reordering, and sampled inter-arrival times (IATs) and round trip times (RTTs). In analysis mode, P4TG measures rates on the input ports, samples IATs, and forwards traffic through its output ports. We compare P4TG’s performance with the one of the software TG TRex and the hardware TG EXFO. P4TG’s code will be provided on GitHub.

Time-Sensitive Networking (TSN) extends Ethernet to enable real-time communication. In TSN, bounded latency and zero congestion-based packet loss are achieved through mechanisms such as the Credit-Based Shaper (CBS) for bandwidth shaping and the Time-Aware Shaper (TAS) for traffic scheduling. Generally, TSN requires streams to be explicitly admitted before being transmitted. To ensure that admitted traffic conforms with the traffic descriptors indicated for admission control, Per-Stream Filtering and Policing (PSFP) has been defined. For credit-based metering, well-known token bucket policers are applied. However, time-based metering requires time-dependent switch behavior and time synchronization with sub-microsecond precision. While TSN-capable switches support various TSN traffic shaping mechanisms, a full implementation of PSFP is still not available. To bridge this gap, we present a P4-based implementation of PSFP on a 100 Gb/s per port hardware switch. We explain the most interesting aspects of the PSFP implementation whose code is available on GitHub1. We demonstrate credit-based and time-based policing and synchronization capabilities to validate the functionality and effectiveness of P4-PSFP. The implementation scales up to 35840 streams depending on the stream identification method. P4-PSFP can be used in practice as long as appropriate TSN switches lack this function. Moreover, its implementation may be helpful for other P4-based hardware implementations that require time synchronization.

Bit Index Explicit Replication (BIER) is an efficient domainbased transport mechanism for IP multicast (IPMC) that indicates receivers of a packet through a bitstring in the packet header. Recently, BIER forwarding has been implemented on 100 Gbit/s per port hardware using the P4 programming language. However, the implementation requires packet recirculation to iteratively serve one next-hop after another. The objective of this paper is to reduce this inefficiency. Static multicast groups can be configured on P4 switches so that traffic can be sent to all next-hops without recirculation. We leverage that feature to make BIER forwarding more efficient. However, only a limited number of static multicast groups can be configured on a switch, which is not sufficient to cover all potential port patterns. In a first step, we develop efficient BIER forwarding that utilizes static multicast groups derived from so-called configured port clusters. Then, we design port clustering algorithms that observe multicast patterns and compute configured port clusters which are more efficient than randomly selected port clusters. These methods are based on Spectral Clustering, an unsupervised machine learning technique. We perform simulations that underline the effectiveness of this approach to reduce inefficient packet recirculations. We further implement the new forwarding behaviour on programmable hardware and provide a controller that samples BIER packets on the switch, runs the port clustering algorithms, and updates the configured static multicast groups. We validate this open source implementation in a testbed and show that the experimental results are in line with the simulation results.