GreenGlue: Power Optimization for Data Centers through Resource-Guaranteed VM Placement

In a data center, virtual machines (VMs) not only require the server resource (e.g., CPU, memory) but also might generate a lot of network traffic among themselves. Existing research works on VMs placement are focusing on (1) how to place VMs to minimize server energy consumption without considering consumption of network resources, or (2) how to minimize inter-VM network traffic without considering energy consumption. In this work, we tackle the power saving issue of data centers from the point of view of VM placement as well, but, our idea is to address VM placement problem by joint consideration of both server and network energy consumption for minimizing total power consumption of a data center. First, we validate that the network power consumption plays an important part on the total power consumption of a data center by analyzing the data center architectures and the power benchmark of IT equipments. Next, we propose an energy-aware VM placement algorithm, called GreenGlue, which jointly optimizes the power consumed by servers and switches. GreenGlue is able to address initial VM placement issue, in which VM requests are given and no running VM exists in a data center. Furthermore, an optimal VM placement model is derived via the mixed integer linear programming. Finally, we present a comprehensive performance study via simulation with different scenarios generated by synthetic and real traffic traces. The results show that GreenGlue can perform better than existing VM placement schemes in terms of the power saving and the rate of finding feasible placement.