The demands for deterministic network services are getting significant. IEEE Time sensitive networking (TSN) task group has aimed for deterministic services through IEEE 802 networks. TSN's solutions rely on the time-synchronization and the slot scheduling coordinated throughout a network. The former requires costly hardware implementations for accuracy and scalability. The latter requires a schedulability analysis, which is proven to be NP-complete and not scalable. For modest-to-large scale dynamic networks, a more flexible solution is necessary. We propose a scalable framework that guarantees any desired jitter upper bound, including zero jitter. The framework is composed of; packets with relative time-stamps, a network that guarantees latency bounds, and buffers at the network egress. The latency bounds of a network can be of any value. The buffer holds packets for predetermined intervals to reproduce arbitrary inter-arrival intervals to inter-departure intervals, based on the network's latency bound. The idea behind the proposed framework is to minimize the latency first with work-conserving schedulers, and then adjust the jitter at the egress of a network. We argue that this is simpler than minimizing latency and jitter at the same time. A direct benefit of such simplicity is its scalability. We examine the network solutions that guarantee latency bound, such as the DiffServ and the Flow aggregate-interleave regulator (FAIR), as the candidates for the component in the framework. We show with a case study and simulations that the proposed framework can guarantee smaller latency bounds, with zero jitter, than those of the TSN's synchronous approach.

Emerging applications such as industrial automation, in-vehicle, professional audio-video, and wide area electrical utility networks require strict bounds on the end-to-end network delay. Solutions so far to such a requirement are either impractical or ineffective. Flow based schedulers suggested in a traditional integrated services (IntServ) framework are O(N) or O(log N), where N is the number of flows in the scheduler, which can grow to tens of thousands in a core router. Due to such complexity, class-based schedulers are adopted in real deployments. The class-based systems, however, cannot provide bounded delays in networks with cycle, since the maximum burst grows infinitely along the cycled path. Attaching a regulator in front of a scheduler to limit the maximum burst is considered as a viable solution. International standards, such as IEEE 802.1 time sensitive network (TSN) and IETF deterministic network (DetNet) are adopting this approach as a standard. The regulator in TSN and DetNet, however, requires flow state information, therefore contradicts to the simple class-based schedulers. This paper suggests non-work conserving fair schedulers, called ‘regulating schedulers’ (RSC), which function as a regulator and a scheduler at the same time. A deficit round-robin (DRR) based RSC, called nw-DRR, is devised and proved to be both a fair scheduler and a regulator. Despite the lower complexity, the input port-based nw-DRR is shown to perform better than the current TSN approach, and to bind the end-to-end delay within a few milliseconds in realistic network scenarios.

In this study, we propose a scalable framework that guarantees both latency and jitter bounds in large networks, including the Internet. The framework is composed of two parts: a latency-guaranteeing network and a jitter-guaranteeing end system. For latency bounds, we suggest regulators per class per input–output port pair of the DiffServ-type relay nodes. For jitter bounds, based on the guaranteed latency bounds, we suggest time-stamping and buffers at the network egress edge. The framework does not require network-wide time synchronization, frequency synchronization, flow state maintenance, or flow-level queuing/scheduling. Therefore, the complexity does not increase as the number of flows or network size increases. Moreover, the framework is based on the DiffServ architecture; therefore, it requires minimal modification to the current Internet. We demonstrate that the proposed regulators can achieve latency bounds comparable to the IEEE asynchronous traffic shaping technique. We prove that the jitter is bounded even with realistic limitations such as buffers without cut-through capability. We also prove that in the presence of clock drift, the jitter can still be upper bounded with a suggested compensation algorithm. We demonstrate through experiments on simple programmable microcontrollers that the jitter upper bound can be within a few tens of microseconds, even in a realistic situation with store-and-forward buffers, clock drift, and random network delays.

Adopting reinforcement learning in the network scheduling area is getting more attention than ever because of its flexibility in adapting to the dynamic changes of network traffic and network status. In this study, a timeslot scheduling algorithm for traffic, with similar requirements but different priorities, is designed using a double deep q-network (DDQN), a reinforcement learning algorithm. To evaluate the behavior of the DDQN agent, a reward function is defined based on the difference between the estimated delay and the deadline of packets transmitted at the timeslot, and on the priority of packets. The simulation showed that the designed scheduling algorithm performs better than existing algorithms, such as the strict priority (SP) or weighted round robin (WRR) scheduler, in the sense that more packets arrived within the deadline. By using the proposed DDQN-based scheduler, it is expected that autonomous network scheduling can be realized in upcoming frameworks, such as time-sensitive or deterministic networking.

We consider guaranteeing end-to-end (E2E) latency bounds to flows in a network. It is desirable that flows are isolated from other flows. The bursts from other flows or the network utilization level should not affect a flow’s latency bound. The fair queuing technique, which includes Packetized Generalized Processor Sharing (PGPS) and Virtual Clock (VC), is based on the concept of ideal packet service completion time called the Finish Time (FT). The fair queuing is known to provide the best flow isolation but suffers from the fact that it has to maintain the flow states. Alternative schemes were suggested, in which the entrance node in a network generates FT for a packet and records it in the packet with other necessary information. Subsequent nodes, based on these records, decide the service eligibility and service order of the packets. A packet is served only when it is eligible, thus the system is non-work conserving. In this paper, a simpler framework for deriving such FTs in core nodes is presented, in which initial FT is updated by adding a delay factor that is a function of parameters of nodes and flow. The proposed scheduler is work conserving and has the property that, for a certain choice of the delay factor, the expression for E2E latency bound can be found. This E2E latency bound function is the same as that of a network with stateful fair queuing schedulers in all the nodes. Moreover, utilizing the fact that the service order of packets passing through the same path can be unaltered in the middle of the path, we also present a FIFO-based architecture whose performance is similar to that of a sorted queue-based architecture. The extensive simulations prove that the proposed framework shows an ideal flow isolation performance over a wide range of delay factor values, with superior scalability.