A new method based on PSR and EA-GMDH for host load prediction in cloud computing system

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• 作者：Qiangpeng Yang (1)
  Chenglei Peng (1)
  He Zhao (1)
  Yao Yu (1)
  Yu Zhou (1)
  Ziqiang Wang (1)
  Sidan Du (1)
  
• 关键词：Host load prediction ; Phase Space Reconstruction ; Group Method of Data Handling ; Evolutionary Algorithm
• 刊名：The Journal of Supercomputing
• 出版年：2014
• 出版时间：June 2014
• 年：2014
• 卷：68
• 期：3
• 页码：1402-1417
• 全文大小：
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• 作者单位：Qiangpeng Yang (1)
  Chenglei Peng (1)
  He Zhao (1)
  Yao Yu (1)
  Yu Zhou (1)
  Ziqiang Wang (1)
  Sidan Du (1)
  
  1. School of Electronic Science and Engineering, Nanjing University, Nanjing, China
  
• ISSN：1573-0484

文摘

Host load prediction is one of the most effective measures for improving resource utilization in cloud computing systems. Due to the drastic fluctuation of the host load in the Cloud, accurately predicting the host load remains a challenge. In this paper, we propose a new prediction method that combines the Phase Space Reconstruction method and the Group Method of Data Handling based on an Evolutionary Algorithm. The performance of our proposed method is evaluated using two real-world load traces. The first is the load trace in a traditional distributed system, whereas the second is in a Google data center. The results show that the proposed method achieves a better prediction performance than some state-of-the-art methods.