  In virtualized data centers, consolidation of Virtual Machines (VMs) on
minimizing the number of total physical machines (PMs) has been recognized as a
very efficient approach. This paper considers the energy-efficient
consolidation of VMs in a Cloud Data center. Concentrating on CPU-intensive
applications, the objective is to schedule all requests non-preemptively,
subjecting to constraints of PM capacities and running time interval spans,
such that the total energy consumption of all PMs is minimized (called MinTE
for abbreviation). The MinTE problem is NP-complete in general. We propose a
self-adaptive approached called SAVE. The approach makes decisions of the
assignment and migration of VMs by probabilistic processes and is based
exclusively on local information, therefore it is very simple to implement.
Both simulation and real environment test show that our proposed method SAVE
can reduce energy consumption about 30% against VMWare DRS and 10-20% against
EcoCloud on average.
