Optimizing virtual machine placement in distributed clouds with M/M/1 servers

As more and more applications migrate into clouds, the placement of virtual machines for these applications has a significant impact on the performance of cloud systems. A number of virtual machine (VM) placement techniques have been proposed over recent years. However, most of the existing works on VM placement ignore the response latency of the requests from tenants. In this paper, we investigate the techniques of VM placement in distributed clouds with stochastic requests from the tenants. We first model the requests for each application from the corresponding tenant as independent Poisson stream. Moreover, based on the analyses of distributed cloud resources, the VMs with their data nodes are modeled as simple M/M/1 queueing systems. Then, we propose the problems of VM placement with two distinct optimization objectives. For each objective, we present the formal definition and prove its NP-hardness. To deal with them, we propose some algorithms and the performances of them are analysed in each section. For applying to the situation of lacking of resource, we propose two extended algorithms. We conduct abundant simulation experiments in distributed cloud environment to evaluate the performance of our proposed algorithms. The simulation results show that the proposed algorithms can significantly improve the performance of their corresponding objectives.