Clustering-based energy-aware virtual network embedding

Abstract

Virtual network embedding has received a lot of attention from researchers. In this problem, it needs to map a sequence of virtual networks onto the physical network. Generally, the virtual networks have topology, node, and link constraints. Prior studies mainly focus on designing a solution to maximize the revenue by accepting more virtual networks while ignoring the energy cost for the physical network. In this article, to bridge this gap, we design a heuristic energy-aware virtual network embedding algorithm called EA-VNE-C, to coordinate the dynamic electricity price and energy consumption to further optimize the energy cost. Extensive simulations demonstrate that this algorithm significantly reduces the energy cost by up to 14% over the state-of-the-art algorithm while maintaining similar revenue.

Service disruption index (SDI): A novel user perspective reliability indicator for modern virtual service networks

“…In the literature, most of the advances in network virtualization concentrate on virtual resource allocation, which is known as the virtual network embedding (VNE) problem. [11][12][13][14][15][16][17][18] Moreover, VNE algorithms deal with the allocation of virtual topology onto substrate infrastructure with regard to different objectives such as cost efficiency, 15 energy efficiency, 16 QoS, 17,18 etc.…”

Energy‐Efficient Virtual Network Embedding Algorithm Based on Hopfield Neural Network

“…This method fixes the attributes during the embedding process and ignores the other node and link attributes that affect the embedding performance. Liu et al [9] proposed a clusterbased collaborative embedding algorithm to optimize the energy consumption. A weighted graph is generated according to the virtual network topology, and it is then clustered with a local clustering algorithm.…”