Abstract
Virtual machine consolidation techniques provide ways to save energy and
cost in cloud data centers. However, aggressive packing of virtual
machines can cause performance degradation. Therefore, it is essential
to strike a trade-off between energy and performance in data centers.
Achieving this trade-off has been an active research area in recent
years. In this paper, a host underload detection algorithm and a new VM
selection and VM placement techniques are proposed to consolidate
Virtual machines based on the growth potential of VMs. Growth potential
is calculated based on the utilization history of VMs. The
interdependence of VM selection and VM placement techniques are also
studied in the proposed model. The proposed algorithms are evaluated on
real- world PlanetLab workload on Cloudsim. The experimental evaluation
shows that our proposed technique reduces Service Level Agreement
Violation (SLAV) and energy consumption compared to the existing
algorithms.