Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (7): 1955-1964.doi: 10.23940/ijpe.19.07.p23.19551964

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Cloud Computing Resource Load Forecasting based on Bat Algorithm Optimized SVM

Yuxia Li*   

  1. Beijing Union University, Beijing, 100025, China
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  • About author:Yuxia Li is an associate professor at Beijing Union University. She received her master's degree from Beijing Institute of Technology. Her research focuses on cloud computing.

Abstract: For the problem of resource load forecasting in cloud computing, the optimized bat algorithm is combined with SVM for forecasting. Firstly, the bat algorithm adopts the reverse learning strategy for population initialization, and secondly, the weighting factor in the particle swarm optimization is used for individual optimization. Finally, the individual is selected using the Gaussian mutation method. Two important parameters in the SVM are optimized using the improved algorithm. In the simulation experiment, the SVM is optimized by the particle swarm optimization and compared with the genetic algorithm optimizing SVM, and a better forecasting effect is obtained.

Key words: cloud computing, resource load, forecasting, bat algorithm