An ACO-based multi-objective optimization for cooperating VM placement in cloud data center.

High-performance computing requires numerous virtual machines (VMs) to meet the demand for services of the end-users. Such computation generates high intra-network traffic among the services running in different VMs. Thus, to achieve a high throughput of the application, VMs are to be deployed in physical machines in a way that reduces the communication cost and delays and thereby meets the high quality of services demanded by the users. On the other hand, the service providers aim to consolidate VMs in a minimum number of active physical machines to reduce their operational costs. Finding an optimal solution to minimize the cost of either the deployment or communication, by themselves are NP-Hard problems. Moreover, an attempt to optimize one disregarding the other may give a solution that is better in terms of cost but inferior in terms of throughput (or vice versa). Hence, we formulate the VM placement problem as a multi-objective optimization problem and propose an Ant Colony Optimization-based VM consolidation algorithm to find a solution in real-time. We have also presented a performance comparison of the proposed algorithm with existing mono-objective and multi-objective algorithms. [ABSTRACT FROM AUTHOR]