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.