Dynamic and highly energy-efficient virtual network embedding method based on elastic optical networks

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.