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A widespread use of the cloud computing paradigm has increased the necessity and significance of improving the management efficiency of cloud data centers. Special attention is paid to solving cloud resource management problems. Due to the intensive changes of virtual machine (VM) workloads and different conditions of resource utilization the VM placement and migration problems should be solved and optimized continuously in an online manner. To address such problems the authors present an approach to continuous new VM allocation and VM migration. The authors also evaluate a particular policy of the VM allocation in a data center using an adaptive genetic algorithm. The proposed Adaptive Software Defined approach to the cloud data centers management is implemented by using the policy selector, that allows to select different algorithms or policies for resources and virtual machines management in order to adapt to the impact of disturbing influences.

The decomposition-compensation method of service level management used in corporate IT infrastructures is proposed in the paper. The method assumes the decomposition of service level management tasks and the compensation of the negative impact of various factors by allocating extra resources for critical applications. The approach is based on the interaction of three integrated hierarchical processes — matching the level of services, resource planning and service level management. For the service level management the adaptive genetic algorithm was used.