Elasticity-Aware Virtual Machine Placement in K-ary Cloud Data Centers

With the increasing popularity of cloud computing, the cloud data center suffers from both limited resources and the variation of users' requests. One important feature of cloud computing is on-demand scaling, enabling the fluctuation of one user's resource demand. However, amongst pre vious work concerning the virtual machine (VM) placement in data centers, satisfying requested resources of VMs is the primary objective, which neglects the future demand variation. In this paper, we propose the concept of elasticity, referring to how well the data center can satisfy the growth of the input VMs' resource demands under both the limitations of physical machines (PMs) capacities and links capacities. In order to consider both dimensions of the machine and bandwidth resources simultaneously, we propose our hierarchical VM placement algorithm. Besides that, we also prove the optimality of our algorithm in a frequently used semi-homogeneous data center configuration. Furthermore, we study the heterogeneous data center configuration, favoring the characteristics of multi-tenant data centers. Evaluation results validate the efficiency of our algorithm. Key wordsElasticity-aware; VM Placement; Data Centers; K-ary Topology