Solution for virtual network embedding problem based on Simulated Annealing genetic algorithm

Assigning the resources of a virtual network to the components of a physical network, called Virtual Network Mapping, plays a central role in network virtualization. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms which had clear separation between the node mapping and the link mapping phases. In this paper we propose a Simulated Annealing genetic algorithm to optimize node mapping, and the heuristic algorithm or multi-commodity flow algorithms to solve the link mapping. Our experimental evaluations show that the proposed algorithm increases the acceptance ratio and the revenue while decreasing the cost incurred by the substrate network in the long run.