Abstract
In the actual cloud computing environment, the approaches to resource scheduling of virtual machines (VM) are focused only on the current state of a whole system. This paper presents a strategy for scheduling based on a genetic algorithm. In accordance with the historical data and the current state of the system, this strategy calculates in advance its impact on the system after the distribution of the required VM resources. The experimental results demonstrate that the strategy provides a better load distribution and reduces dynamic migration.
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