Resource Allocation Algorithm Based on Dynamic Quantitative Impairment With Low-Fragmentation in SDM-EONs

Space division multiplexing elastic optical networks (SDM-EONs) is a promising solution to enhance the transmission capacity of optical networks. However, physical layer impairments (PLIs) degrade the service's quality of transmission (QoT). Additionally, service-differentiated spectrum demand...

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Veröffentlicht in:Journal of lightwave technology Jg. 43; H. 18; S. 8525 - 8537
Hauptverfasser: Ren, Danping, Yang, Haoyu, Bao, Bowen, Yao, Qiuyan, Hu, Jinhua, Zhao, Jijun, Yang, Hui
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 15.09.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Computational modeling
core
Elastic optical networking with space division multiplexing
Estimation
Fragmentation
Heuristic algorithms
Impairment
Multiplexing
Noise
Optical fiber amplifiers
Optical fiber networks
Optical fibers
physical layer impairment
quality of the transmission
Quality of transmission
Resource allocation
Resource management
Routing
Spectrum allocation
spectrum fragmentation
ISSN:0733-8724, 1558-2213
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Zusammenfassung:Space division multiplexing elastic optical networks (SDM-EONs) is a promising solution to enhance the transmission capacity of optical networks. However, physical layer impairments (PLIs) degrade the service's quality of transmission (QoT). Additionally, service-differentiated spectrum demand leads to spectrum fragmentation, which is further aggravated by strict PLI constraints. Therefore, we propose a routing, core and spectrum allocation algorithm based on dynamic quantitative impairments for low fragmentation (QISEN-LowSF) in SDM-EONs. This algorithm quantitatively analysis multiple impairments and designs restrictive condition to weaken the fragmentation. Specifically, we design a path selection mechanism that takes transmission distance and integration degree of path resources as the cost metrics. Then, we abstract multiple impairment effects in core, and design a core selection mechanism at the cost of impairment estimation and resource integration of each core. When spectrum is allocated to the service, we design a reduced fragmentation spectrum allocation strategy based on the combination of quantified impairment with low-fragmentation. We also optimize the service impairment estimation model in the QoT calculation phase. The results show that QISEN-LowSF performs better than the comparison algorithms under different traffic loads. From the above, the QISEN-LowSF algorithm has superior dynamic flexibility and can reduce blocking probability and the resource fragmentation. Further, it can effectively handle various traffic loads.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0733-8724
1558-2213
DOI:10.1109/JLT.2025.3595151