Energy-performance tradeoffs in IaaS cloud with virtual machine scheduling

In the cloud data centers, how to map virtual machines (VMs) on physical machines (PMs) to reduce the energy consumption is becoming one of the major issues, and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements. However, the aggressive consolidation of these resources may lead to network performance degradation. In view of this, this paper proposes a two-stage VM scheduling scheme: (1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs, we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance. This scheme makes a tradeoff between energy efficiency and network performance. We design a new two-stage heuristic algorithm for a solution, and the simulations show that our solution achieves good results.