Energy-aware Management of Virtual Machines in Cloud Data Centers

ABSTRACT

The demand for more resources in computational power, memory and disk storage by modern applications and enterprises, results in the consumption of huge amounts of electrical power at cloud data centers. Consequently, cloud service providers, should not only attempt to provide competitive services to their customers, but also keep at the same time their operational costs at acceptable levels by minimizing energy consumption. The reduction of the number of active servers, using live virtual machine (VM) migrations, while keeping the system performance within the levels specified by the SLAs with customers, are main objectives of cloud service providers towards the above goals. In this paper, an efficient VM provisioning mechanism for cloud data center environments is proposed. We first describe our proposed VM allocation policy and then perform a series of simulation experiments based on CloudSim [1] toolkit. Simulation results show that all variations of our proposed provisioning mechanism behave better, in terms of energy consumption and reduction of SLA violations, than the well-known and efficient LrMmt provisioning mechanism [2].

References

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Index Terms

• Computer systems organization

  • Dependable and fault-tolerant systems and networks

• Computing methodologies

  • Machine learning

    • Machine learning approaches

      • Neural networks

• General and reference

  • Cross-computing tools and techniques

    • Performance

• Hardware

  • Emerging technologies

    • Circuit substrates

      • Cellular neural networks

• Networks

  • Network performance evaluation

• Software and its engineering

  • Software notations and tools

    • Compilers

• Theory of computation

  • Theory and algorithms for application domains

    • Machine learning theory