Applied Sciences (Oct 2023)

Traffic-Driven Proactive Slot Orchestration in an Optical Network with Fine-Granularity Flexible Ethernet Interfaces

  • Qian Hu,
  • Zixuan Wang,
  • Xin Qin,
  • Zexi Zhou,
  • Guangnan Su,
  • Wenwu Zhu,
  • Rentao Gu

DOI
https://doi.org/10.3390/app132011398
Journal volume & issue
Vol. 13, no. 20
p. 11398

Abstract

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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.

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