The integration of 5G and vertical industries promotes the development of the energy Ethernet while putting forward fine granularity, flexibility, high reliability, and deterministic low-latency service requirements for the smart grid and the ubiquitous power Internet of Things (UPIoT). As the bearer architecture supporting the next-generation optical transmission network, the Slicing Packet Network (SPN) slice granularity decreases from 5 Gbps to 10 Mbps fine granularity and the frame period of 5 Gbps large-granularity slices is short, so the non-deterministic delay caused by timeslot conflicts has a negligible impact on the end-to-end delay, and the timeslot scheduling is unnecessary. However, due to the reduction in timeslot granularity and the change in frame structure in 10 Mbps slices, the scheduling of conflicting timeslots and the complex device computing management problems need to be solved urgently. In this paper, we establish a model of routing embedded timeslot scheduling for the routing of fine-granularity slices and timeslot scheduling problems in SPN-based FlexE interfaces, for which we propose a deterministic timeslot allocation mechanism supporting end-to-end low-latency transmission. According to the timeslot symmetry, the mechanism can reduce the space of feasible solutions through ant colony optimization and unidirectional neighborhood search (ACO-UNS), so as to efficiently solve the scheduling of conflicting timeslots and provide end-to-end delay guarantee for delay-sensitive services. Finally, we make a comparison between the ACO-UNS algorithm and the timeslot random dispatching algorithm (ACO-RD); the results show that, relative to the ACO-RD, the reduction in the proposed ACO-UNS is 98.721% for the end-to-end delay of fine-granularity slices.

With the continuous emergence of the concept of 6G, the rapid development of industrial application scenarios, and the rise in demand for dedicated line services, there has been a strong and diverse demand for network capacity. The introduction of fine-granularity FlexE technology provides a new approach to addressing the diversification of Quality of Service (QoS) and the resource waste caused by large granularity (5 Gbps). However, the reduction in granularity leads to a significant increase in the number of slots, posing a serious challenge to deterministic latency assurance, especially in scenarios with dynamic fluctuations in service bandwidth. Sudden bandwidth variations can lead to service interruptions and fluctuations, resulting in uncontrolled network blocking rates. To address this issue, this paper proposes a traffic-driven proactive FlexE slot orchestration algorithm called PMFAN-GDSO. Based on this algorithm, bandwidth variations are calculated in advance based on the bandwidth change provided via the traffic prediction algorithm before service fluctuations occur. This avoids the time-consuming slot orchestration calculations and service abrupt changes. The real-world network datasets indicate that, based on our proposed algorithm, significant time savings of up to 46.8% are achieved compared to non-proactive prediction.