A Novel Method for Virtual Network Embedding with Incentive Convergence Mechanism

One of the main challenges of network virtualization is efficient mapping of virtual nodes and virtual links onto the substrate network resources, which is known as virtual network embedding (VNE) problem. This paper aims to increase the revenue and utilization of infrastructure provider as well as achieve efficiency mapping. Due to the NP-hard character of VNE, we model the VNE problem as an integer linear programming problem and adopt a DPSO-based heuristic algorithm to solve the problem, the operations and parameters of the particles are well redefined according to the VN embedding context. Considers the mapping complexity, an incentive convergence mechanism is proposed before embedding a virtual network onto the substrate network. In this mechanism we use individual candidate physical nodes and reusable mapping technology to accelerate convergence and save more bandwidth during virtual network mapping. Simulation results show that the proposed algorithm is superior to existing similar algorithms in the physical network resource utilization, revenue/cost ratio and searching efficiency.