Abstract
Cloud computing resource scheduling efficiency is the direction of the current research. In this paper, we first set up a resource scheduling model in cloud computing environment, and put the individual and the cloud computing node resources in the firefly algorithm. Secondly, in individual initialization algorithm introduced genetic algorithm optimize the initial solution, on location algorithm update setting sensory threshold used to adjust the individual probability of selecting the optimal path. Finally, the improvement of the volatile factor makes the value of the fluorescence to be updated. Simulation results show that the proposed algorithm can effectively improve the performance of resource scheduling in cloud computing, shorten the time to complete the task, and improve the overall processing capacity of the system.
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