An Ant Colony Optimization Algorithm for Virtual Network Embedding

摘要

Virtual network embedding that embedding virtual network in substrate network is usually mentioned as resource allocation problem in network virtualization. Virtual network embedding can be employed to solve the problems like resource constraint, access control, request online and diversity of topology. This paper develops an ant colony optimization algorithm of virtual network embedding (ACO-VNE). The ants secrete and update pheromones in node mapping according to the cost of link mapping. Based on feedback information, the ants move to find good solution through learning from each other. Simulation results suggest that the algorithm can map the virtual network with low rejection rate and high revenue of substrate network.