20 December 2021 Dynamic and highly energy-efficient virtual network embedding method based on elastic optical networks
Zhidong Zhang, Shan Yin, Jingjing Wu, Shanguo Huang
Author Affiliations +
Abstract

Network virtualization has been considered one of the promising paradigms for future network architecture, which can satisfy the diversified and personalized requirements of different applications by sharing physical network infrastructure. One of the major challenges in virtualization is how to map virtual networks efficiently onto the substrate network considering different constraints. We aim at solving the problem of high energy consumption of virtual network embedding in respect of the orthogonal frequency division multiplexing using elastic optical networks (EONs). First, we comprehensively consider and design an energy consumption model of network components, which denotes the key part of virtual optical network embedding (VONE). Then, a dynamic heuristic energy-efficient virtual optical network embedding (DEE-VONE) algorithm is proposed to achieve high energy efficiency and resource scalability. Simulation experiments have proven that, compared with the two benchmark algorithms, namely, the FFK-VONE and LRCK-VONE, the proposed method can maximize the network energy consumption saving at the cost of increasing the blocking probability. As the traffic load increases, the DEE-VONE method achieves higher energy-saving efficiency because optical switching energy saving plays an essential role.

© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2021/$28.00 © 2021 SPIE
Zhidong Zhang, Shan Yin, Jingjing Wu, and Shanguo Huang "Dynamic and highly energy-efficient virtual network embedding method based on elastic optical networks," Optical Engineering 60(12), 126106 (20 December 2021). https://doi.org/10.1117/1.OE.60.12.126106
Received: 23 July 2021; Accepted: 1 December 2021; Published: 20 December 2021
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KEYWORDS
Optical networks

Energy efficiency

Optical engineering

Roentgenium

Networks

Modulation

Network architectures

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