Abstract
Cloud computing can provide Virtual Machine (VM) computing resources to meet the growing computational demands. In this paper, we propose a scheduling strategy based on an Improved Genetic Algorithm (IGA) for independent task in Cloud Computing environment. Especially, the IGA scheduling strategy can shorten the completion time of the tasks with priority as well as total completion time. Our scheduling strategy based on IGA performs better than other original scheduling strategies such as the Random, Rotating and Greedy in open-source platform, which have been proved by the simulation results in the CloudSim toolkit. It also shows the IGA is better robust than the standard GA when the load and computing power are extremely unbalanced.
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