7 August 2018 Distance-adaptive fragmentation-avoiding spectrum resource allocation for unicast service in flexible optical networks
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Abstract
Flexible optical networks (FONs) are used to handle the enormous bandwidth demands and significantly improve the flexibility and efficiency of spectrum resources. This flexibility opens the door to strategies that can optimize the allocation of spectrum resources. The dynamic setup and teardown of traffic will inevitably fragment these resources and increase the network blocking probability. Different modulation formats can be configured to guarantee efficient spectrum resource allocation by taking the transmission distance into account. We investigated routing and fragmentation-avoiding spectrum allocation for the unicast service over FONs with the constraints of spectrum resource and transmission distance. To alleviate spectrum fragmentation, the available spectrum adjacency (ASA) is used to estimate the adjacency among available spectrum block resources on routing paths or links. A distance-adaptive fragmentation-avoiding spectrum resource allocation (DA-FASA) algorithm based on ASA and genetic operators is proposed to resolve the spectrum fragmentation problem in FONs. The DA-FASA algorithm defines an ASA value for the free spectrum blocks on each routing path and each modulation format to maximize spectrum availability, which effectively reduces the spectrum fragmentation and network congestion. Simulation results indicate that DA-FASA exhibits highly efficient performance with regard to the bandwidth blocking probability and the spectrum utilization ratio under different network scenarios, compared to the benchmark algorithms.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2018/$25.00 © 2018 SPIE
Yanxia Tan, Rentao Gu, Jiabin Cui, Dajiang Wang, Hongbiao Li, and Yuefeng Ji "Distance-adaptive fragmentation-avoiding spectrum resource allocation for unicast service in flexible optical networks," Optical Engineering 57(8), 086104 (7 August 2018). https://doi.org/10.1117/1.OE.57.8.086104
Received: 12 April 2018; Accepted: 19 July 2018; Published: 7 August 2018
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Fermium

Optical networks

Frequency modulation

Modulation

Genetics

Networks

Computer simulations

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