Energy-Driven Virtual Network Embedding Algorithm Based on Enhanced Bacterial Foraging Optimization

Abstract

One of the core challenges facing network virtualization is how to manage the underlying resources to host more virtual networks (VNs) with less energy. With the goal of reducing the energy consumption of virtual network embedding (VNE) and ensuring the VNE solution validity, this paper presents a new approach based on the bacterial foraging optimization (BFO) algorithm devoted to using the underlying resources more effectively and reasonably. In particular, by mimicking the information interaction between bacteria in the process of foraging, we devise a topology-aware mapping strategy, known as SBR_E, to build the candidate set of the VNE solutions. Then, we leverage SBR_E to design the energy manager of the optimization process and develop an energy-driven VNE algorithm based on BFO identified as EBFO to search for the optimal solution. Experimental results show that our method is superior to the existing algorithms in terms of reducing energy consumption and improving the VN request acceptance rate and revenue-cost ratio.