Energy-Aware on-chip virtual machine placement for cloud-supported cyber-physical systems

Recent trends in the design of cyber-physical systems (CPS) are moving towards heterogeneous multi-core architectures with cloud support. In this paper, we propose an energy-aware scheme for virtual machine placement in cloud-supported CPS with Network-on-Chip (NoC) architecture. We formulate the energy-aware on-chip virtual machine placement problem as an optimization problem, and design a heuristic scheme based on ant-colony optimization. We address problems of slow convergence speed and easily falling into stagnation in ant-colony algorithm by employing pheromone diffusion model that makes the proposed scheme more efficient. Simulation results show that our scheme achieves much higher energy efficiency compared with previous schemes with different network sizes and traffic models.