Energy efficient virtual network embedding for green data centers using data center topology and future migration

With the rapid proliferation of data centers, their energy consumption and greenhouse gas emissions have significantly increased. Some efforts have been made to control and lower energy consumption of data centers such as, proportional energy consuming hardware, dynamic provisioning, and virtualization machine techniques. However, it is still common that many servers and network resources are often underutilized, and idle servers spend a large portion of their peak power consumption. We first build a novel model of virtual network embedding in order to minimize energy usage in data centers for both computing and network resources by taking practical factors into consideration. Due to the NP-hardness of the proposed model, we develop a heuristic algorithm for virtual network scheduling and mapping. In doing so, we specifically take the expected energy consumption at different times, virtual network operation and future migration costs, and a data center architecture into consideration. Our extensive evaluation results show that our algorithm could reduce energy consumption up to 40% and take up to a 57% higher number of virtual network requests over other existing virtual mapping schemes.