Abstract
For the load imbalance of resource scheduling, an algorithm based on improved genetic algorithm is proposed after the research of resource load scheduling model based on Cloud Computing. The algorithm designed the fitness function, which uses the spatial utilization rate, load changes and the weight, selected individual by the Roulette Wheel Method, and optimized the crossover and mutation operations. Experiment results demonstrate that the algorithm not only can accelerate convergence of load balance scheme, but also has less migration time. It provides a new solution for the research of load balance and virtual Machine Resource Scheduling Strategy.
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Nie, J. (2016). A Research of Virtual Machine Resource Scheduling Strategy Based on Cloud Computing. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_30
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DOI: https://doi.org/10.1007/978-981-10-0356-1_30
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