With the rise of autonomous driving, the performance requirements for In-vehicular networks are continuously increasing. Existing research leverages Frame Replication and Elimination for Reliability (FRER) and Time-Aware Shaper (TAS) mechanisms in Time-Sensitive Networking (TSN) to achieve deterministic transmission. FRER requires transmitting flows over multiple disjoint paths. However, FRER lacks redundancy degree selection strategies, and the delay differences between redundant paths lead to packet disorder, which increases network resource overhead and compromises traffic QoS. In this paper, we propose a Bandwidth-Aware with Frame Replication and Elimination for Reliability (BA-FRER) algorithm dynamically selects redundancy degree based on the current network bandwidth resources, delay, and reliability utility function. Additionally, we propose a Redundant-Aware Order Preservation (RAOP) algorithm configures time slots for each flow based on the TAS mechanism to align the delays of redundant paths. The evaluation results show that the BA-FRER algorithm improves the utilization of network bandwidth resources, the flow access rate, and the reliability, while the RAOP algorithm reduces the probability of packet disorder.

With the rise of critical applications like autonomous systems and remote healthcare, ultra-reliable networks have become indispensable. IEEE 802.1CB Frame Replication and Elimination for Reliability (FRER) protocol is prevalent in Time-Sensitive Networks (TSN). FRER utilizes multiple disjoint paths as redundant routes to ensure the reliability of time-sensitive streams. However, the multi-path in FRER may induce packet burst due to the different delays between paths, and the reliability of TSN may degrade when disjoint paths are absent. In this paper, we propose a delay duration difference model with a novel metric to evaluate the degree of packet burst when streams converge. We design a reliability calculation model that allows for more accurate reliability assessments in TSN with non-disjoint redundant paths. Moreover, we design a Burst and Junction-node Optimization Routing (BJOR) algorithm that stands apart from prior studies by uniquely addressing packet burst and the scenario of non-disjoint paths within FRER. Through evaluations against other state-of-the-art algorithms in TSN, our approach effectively reduces packet burst and significantly enhances the reliability of TSN across various topologies.

The emergence of new time-sensitive networking (TSN) technologies empowers almost-deterministic ultra-reliable low-latency communications for industrial cloud-fog automation paradigms. However, current heterogeneous networks struggle to balance time-sensitivity and flexibility, particularly in mixed-flow scenarios. Existing scheduling approaches within 5G-TSN integration model either suffer from quality of service (QoS) flow mismatch or microbursts. This paper proposes a class-aware mixed-flow scheduling (CAMFS) strategy to enable domain-specific resource allocation in a hybrid wired-wireless TSN, while meeting the differentiated time-sensitive (TS) requirements. A time-triggered multiple cyclic-queuing (TTMCQ) shaper is designed to effectively align the classified and regulated mixed flows from TSN domains to 5G QoS flows through class-aware mapping. We also introduce an anti-starvation resource optimization method that minimizes the total average idle resources resulting from temporal-spatial resource over-provisioning within reserved TS windows (RTWs). Additionally, we present a CAMFS algorithm aimed at enhancing schedulability and resource utilization by sorting mixed flows based on a combination of flow features. Finally, simulation results show that CAMFS exhibits outstanding scheduling performance in terms of end-to-end service latency, scheduling success ratio, and normalized resource distribution compared to other state-of-the-art methods.

With the rapid growth of network speed, datacenter applications have increasing demands on networks for high throughput and ultra-low latency. RDMA is widely deployed due to its high performance. Most existing RDMA congestion control schemes employ end-to-end architecture with inherent feedback delays of at least one Round-Trip Time (RTT).To overcome these limitations, we propose RACC, a rapid and accurate INT-Based RDMA congestion control scheme. The switches directly provide INT feedback, reducing the feedback signal latency. In addition, the adaptive rate update mechanism is adopted at the sender, which enhances the rapid response to network congestion and the stable control of in-flight bytes. We conduct simulation experiments based on the Fat-Tree topology to analyze the requirements for datacenter performance metrics including convergence, fairness, and dynamic queues. Our evaluations show that the peak queue lengths are reduced by up to 80% compared to HPCC and PowerTCP, and the convergence time after congestion is reduced by half.

The emerging space-terrestrial integrated network (STIN) assumes a pivotal role within the 6G vision, promising to deliver seamless global coverage and connectivity. Achieving advanced, high-reliability, and time-sensitive (TS) services in a resource-constrained and failure-prone space environment is critical, but also presents challenges. Existing space-terrestrial communication approaches either suffer from temporary link failures with unstable reliability, or intolerable service latency due to the extensive coverage and uneven traffic distribution. This paper presents FastTS, a heuristic resilient and performant scheduling strategy to achieve fault-tolerant and time-sensitive scheduling in futuristic STINs. First, we model the high-dynamic and failure-prone topology in space, and formulate the scheduling problem as a mixed non-linear problem with the objective of minimizing the average task completion time. To approach the optimal solution, joint time-variant routing and frame replication and elimination for reliability (FRER) redundancy under resource constraints are formally considered in our design. During the path-stable duration, FastTS prioritizes the multipath selection with higher redundancy scores, all while ensuring a bounded low latency for TS services based on time-sensitive networking (TSN) techniques. Specifically, our FastTS is divided into three phases: time-sensitive multipath generation (TMG), series-parallel redundancy scoring (SPRS), and SPRS-based time-variant routing (STR). Finally, simulation results show that FastTS exhibits outstanding performance improvements in terms of packet delay, scheduling success ratio, task completion time and packet loss rate, when compared to other state-of-the-art methods.

The emerging time-critical applications pose intense demands for enabling large-scale deterministic networks. In this paper, we propose a new Programmable Cycle-Specified Queue (PCSQ) for wide-area deterministic packet scheduling. We implement the first end-to-end high-precision rotation dequeuing, which enables microsecond-level time slot resource reservation (noted as T) and especially jitter control of up to 2T. We prototype the PCSQ scheduler on an FPGA. The PCSQ-enabled switches can guarantee bounded delay and jitter transmission on a realistic testbed.