Traffic-Driven Proactive Slot Orchestration in an Optical Network with Fine-Granularity Flexible Ethernet Interfaces  
[PERSON]  
1 State Key Laboratory of Optical Fiber and Cable Manufacturing Technology, China Telecom Research Institute, Beijing 100032, China; [EMAIL_ADDRESS] (X.Q); [EMAIL_ADDRESS] (G.S)  
[PERSON]  
2 School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; [EMAIL_ADDRESS] (Z.W. ); [EMAIL_ADDRESS] (Z.Z. ); [EMAIL_ADDRESS] (W.Z. ); [EMAIL_ADDRESS] (R.G.) [PERSON]  
1 State Key Laboratory of Optical Fiber and Cable Manufacturing Technology, China Telecom Research Institute, Beijing 100032, China; [EMAIL_ADDRESS] (X.Q); [EMAIL_ADDRESS] (G.  
FlexE operates at the physical layer of the network stack, enabling the dynamic partitioning of Ethernet links into sub-links [6; 7]. These sub-links, referred to as \"FlexE groups\", are configurable with respect to their bandwidth allocation, providing a level of flexibility unprecedented in traditional Ethernet architectures [8]. The key innovation lies in the ability to allocate and manage bandwidth in increments as small as 10 Mbps, allowing for fine-grained control over network resources. Moreover, FlexE introduces the concept of \"slots\", allowing for the precise allocation of bandwidth resources within a FlexE group. Each slot corresponds to a discrete unit of time during which a specific amount of bandwidth is available for the data transmission. This temporal granularity enhances the adaptability of the network to varying traffic patterns, ensuring the efficient utilization of resources in scenarios characterized by dynamic and bursty traffic [9]. Upon the arrival of a service within a network slicing, ensuring Quality of Service (QoS) for distinct services mandates the proper allocation of route paths contingent upon the extant network status, coupled with the provision of corresponding time slot resources along each link [10]. The transition from a granularity of 5 Gbps to 10 Mbps engenders the introduction of a pioneering fine-granularity unit (FGU) sublayer within the FlexE frame structure. This introduction, in tandem with the further segmentation and reutilization of FGUs for 5 Gbps time slots, precipitates an exponential augmentation in the number of time slots managed per link. The reduction in granularity accentuates the salience of the non-deterministic delay induced by time slot conflicts, rendering it non-negligible. Additionally, the dynamic fluctuation in service bandwidth presents a formidable challenge for expeditious and dependable time slot reallocation. The surpassing of the prescribed service bandwidth thresholds may necessitate not only the assignment of slot resources, but could also exert an influence on routing determinations, potentially instigating momentary service interruptions and fluctuations. In recent years, traffic prediction technology has garnered widespread application in improving network decision-making along with the variation in the dynamic traffic trends. Empowered via the a priori knowledge afforded by traffic prediction, networks are aptly poised to proactively extend resource computation and bandwidth reservation for the network service. Ensuring QoS for latency-sensitive services is contingent upon the imperative design of a time slot scheduling apparatus tailored for 10 Mbps fine-granularity slices, alongside a time slot reallocation mechanism underpinned by traffic prediction. In this study, we address fine-granularity flexible ethernet slot orchestration for dynamic service scenarios based on proactive multi-flow assisted service awareness. We propose a proactive multi-flow assisted attention-based neural network (PMFAN) for high-accuracy service traffic prediction. Building upon service-awareness information, we further present a genetic algorithm-based deterministic slot orchestration algorithm (GDSO) to support end-to-end low-latency transmission, resolving the slot scheduling challenge posed by dynamic traffic requirements.