Power-Aware Lightpath Management for SDN-Based Elastic Optical Networks

Xiong, Yu; Shi, Jin; Yi, LV; Rouskas, George N.

doi:10.1109/icccn.2017.8038398

Cited by 6 publications

(8 citation statements)

References 22 publications

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“…Results confirm this approach outperforms RSA algorithms that do not make use of historical information. A backpropagation neural network is also used for traffic prediction by Xiang et al [128]. They propose this technique in the context of centralized lightpath management in inter-datacenter EONs, with the aim of reducing switching power consumption by eliminating unnecessary lightpath termination and re-establishment operations.…”

Section: Connection Establishmentmentioning

confidence: 99%

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Mata

Miguel

Durán

et al. 2018

Optical Switching and Networking

336

174

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Artificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.

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Section: Connection Establishmentmentioning

confidence: 99%

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Mata

Miguel

Durán

et al. 2018

Optical Switching and Networking

336

174

View full text Add to dashboard Cite

show abstract

“…A large variety of meta-heuristic algorithms such as ACO [183][184][185][186][187][188][189][190][191], EAs [192][193][194], GAs [195][196][197][198][199][200][201][202][203], PSO [204][205][206][207][208][209], SA [210][211][212], bee colony optimisation-based [213,214], whale optimisation [215,216], FFO [217], BA [85], TLBO [87] and GWO [207] were used in SDN.…”

Section: Meta-heuristic Algorithms Used In Sdnmentioning

confidence: 99%

“…It is used for routing [204,205], resource management [206], multi-tenant virtual network customisation [218], multi-class routing [208] and detection of DDoS attacks [209].…”

Section: Pso In Sdnmentioning

confidence: 99%

“…Xiong et al . [205] proposed, PALM, power‐aware light‐path management algorithm for traffic prediction in SDN‐based elastic optical networks. The goal here is to avoid tearing down a light‐path that becomes idle and takes into consideration reducing the switching power, which is required for re‐establishment of a light‐path again in short time later.…”

Section: Artificial Intelligence In Sdnmentioning

confidence: 99%

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Artificial intelligence enabled software‐defined networking: a comprehensive overview

2019

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Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

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“…A large variety of meta-heuristic algorithms such as ant colony optimization [187][188][189][190][191][192][193][194][195], evolutionary algorithms [196][197][198], genetic algorithms [199][200][201][202][203][204][205][206][207], particle swarm optimization [208][209][210][211][212][213], simulated annealing [214][215][216], bee colony optimizationbased [217,218], whale optimization [219,220], firefly optimization [221], bat algorithm [88], teaching-learning-based optimization [90] and grey wolf optimization [222] were used in SDN.…”

Section: Meta-heuristic Algorithms Used In Sdnmentioning

confidence: 99%

Artificial Intelligence Enabled Software Defined Networking: A Comprehensive Overview

Latah,

Toker

2018

Preprint

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Software defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller, that can be programmed and used as the brain of the network. Recently, the research community has showed an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, we provide a detailed overview of the recent efforts to include AI in SDN. Our study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work we investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

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Power-Aware Lightpath Management for SDN-Based Elastic Optical Networks

Cited by 6 publications

References 22 publications

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Artificial intelligence enabled software‐defined networking: a comprehensive overview

Artificial Intelligence Enabled Software Defined Networking: A Comprehensive Overview

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