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A Virtual Machine Scheduling Strategy Based on Grouping Genetic Algorithm in Cloud Environment

With the emergence of cloud computing, data center is becoming resource pooling and the applications are becoming multi-tenant and heterogeneous which make the server resource load balancing problem become more and more important. In order to resolve contradiction between the heterogeneous applications and sharing resource pool, we think this problem as a multi-dimensional variable vector packing model. For the NP-hard feature, we design a virtual machine scheduling strategy and it resolve the data center resource balancing problem. The experiment indicated that the algorithm can reduce the number of open physical machine to get the most of it and it not affect the physical machine utilization rate and interior load balancing.