Flexible Ethernet Traffic Restoration in Multi-layer Multi-domain Networks

Koulougli, Dahina; Nguyen, Kim Khoa; Cheriet, Mohamed

doi:10.1109/icc42927.2021.9500270

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…pology. The iterative equation of the global pheromone concentration is shown in (16), and the computation of Δ𝜆 (𝑖, 𝑗, 𝜔) is shown in (17).…”

Section: Resultsmentioning

confidence: 99%

“…It introduces mixed integer linear programming (MILP) and integer linear programming (ILP) models for single-hop and multi-hop scenarios, respectively, and presents highly time-efficient approximation algorithms that provide solutions closely approaching the optimal ones in large-scale planning. Based on [12,14], D. Koulougli et al [16] investigated the FlexE Traffic Restoration (FTR) problem that aims to maintain high network utilization via the fast recovery of FlexE clients with the minimum cost using the spare capacity in the already deployed PHYs. And, based on [13], P. Zhu et al [17] introduced a cross-layer security design for FlexE over WDM networks, specifically addressing eavesdropping threats at the physical layer.…”

Section: Related Workmentioning

confidence: 99%

“…The behavioral characteristics of ant colonies show that when ants are blocked or reach their destination, a part of the pheromone will be left on each link, and the pheromone will evaporate over time to update the pheromone concentration of the whole topology. The iterative equation of the global pheromone concentration is shown in (16), and the computation of ∆λ q (i, j, ω) is shown in (17).…”

Section: Pheromone Updatementioning

confidence: 99%

See 2 more Smart Citations

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

Hu,

Wang,

Qin

et al. 2023

Applied Sciences

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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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“…pology. The iterative equation of the global pheromone concentration is shown in (16), and the computation of Δ𝜆 (𝑖, 𝑗, 𝜔) is shown in (17).…”

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Pheromone Updatementioning

confidence: 99%

See 1 more Smart Citation

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

Hu,

Wang,

Qin

et al. 2023

Applied Sciences

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“…On the other hand, the flexibility of FlexE can enhance the network restoration. D. Koulougli et al investigate the FlexE Traffic Restoration (FTR) problem, which aims to maintain high network utilization with the fast recovery of FlexE clients with the minimum cost using the spare capacity in the already deployed PHYs [23]. M. Wu et al proposed an auxiliary graph (AG)-based algorithm to solve the cross-layer restoration (CLR) problem in FlexE-over-EON, which effectively reduces the OPEX [24].…”

Section: Related Workmentioning

confidence: 99%

Routing and Timeslot Scheduling for SPN Fine-Granularity Slices

Yang

Zhang

et al. 2023

Photonics

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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.

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