Topology and migration-aware energy efficient virtual network embedding for green data centers

Abstract

With the rapid proliferation of data centers, their energy consumption and green house 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 virtual-ization 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 built a novel model of a network virtualization 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 have developed a heuristic algorithm for virtual network scheduling and mapping, considering expected energy consumption at different times, a data center architecture, and virtual network migration, as well as operation costs. Our evaluation results show that our algorithm could reduce energy consumption up to 40%, and take up to 57% higher number of virtual network requests over other existing virtual mapping schemes.