Incorporating energy and load balance into virtual network embedding process

Virtual network embedding has propounded as one of the most important techniques to address the issue of Internet architecture ossification. Previous studies on virtual network embedding algorithms focus primarily on the revenue of service providers (SPs) and the acceptance ratio of virtual network requests (VNRs), regardless of the energy consumption for substrate nodes and substrate links. To deal with this issue, some of researchers proposed energy-aware virtual network embedding algorithm to do a tradeoff between the revenue and energy consumption. However, the problem of virtual network embedding is a multi-objective optimization problem, which should take into account the multiple factors such as revenue, energy consumption, quality of services (QoS), load balancing of nodes and links, and so on. In this paper, we incorporate node energy consumption and node resource utilization into the embedding potential computation for substrate nodes, and propose a comprehensive node ranking method called CNRM to measure the substrate node importance. In addition, we utilize an improved differentiated pricing strategy to assign different weights to substrate links according to their resource utilization ratios, adopt the shortest path algorithm to select substrate path with the minimum energy consumption for virtual link during the link mapping process. Extensive simulation results demonstrated that our algorithm achieves a better tradeoff among the acceptance ratio, revenue/cost ratio, energy consumption and network load balance.