A fast ant colony optimization based embedding algorithm for virtual network

Abstract

Aiming at optimizing the efficiency of resource utilization, a new fast ant colony optimization based embedding algorithm for virtual network (VNE-FACO) is proposed under the assumption that substrate network doesn't needs to support the path splitting. By introducing the Gaussian process model, the convergence rate of ant colony optimization algorithm is accelerated to meet the practical real-time requirements. The resource cost of virtual network embedding is considered as the fitness function and the parameters are redefined according to the embedding problem. Experimental results show that VNE-FACO can reduce the computation time significantly with the same accuracy compared with existing researches. © 2013 Binary Information Press.