Elastic, on-line and network aware Virtual Machine placement within a data center

This article presents a new model and a resolution algorithm, based on Tabu Search, for the assignment of Virtual Machines (VMs) to servers in a data center. We propose a Mixed Integer Programming (MIP) model that optimizes the Quality of Service (QoS) and power consumption of applications, taking into account their communication traffic and dynamic aspects. A hierarchic method and a Tabu Search heuristic that considers the network topology are developed to solve cases with realistic sizes—e.g., a data center with 1600 servers per pod, for up to 128,000 total servers—. The method specifically considers the optimal mapping of the application graph into the data center network. The proposed scheduler is compared with 1) a static method that does not consider workload variations, and 2) the first-fit policy as a sample of methods that do not consider communication traffic among VMs.