Elasticity-aware virtual machine placement for cloud datacenters

With the increasing popularity of cloud computing, the cloud datacenter 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 previous work concerning the virtual machine (VM) placement in datacenters, satisfying the VMs' requested resources of users is the primary objective, neglecting future demand variation. In this paper, we propose the concept of elasticity, referring to how well the datacenter can satisfy the growth of the input VMs resource demands under both the limitations of physical machines (PMs) capacities and links capacities. To consider both dimensions of the machine and bandwidth resources simultaneously, we propose our hierarchical VM placement algorithm. We also prove the optimality of our algorithm in a frequently used semi-homogeneous datacenter configuration. Furthermore, we study the heterogeneous datacenter configuration, favoring the characteristics of multi-tenant datacenters. Evaluation results validate the efficiency of our algorithm.