Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (9): 238-245.doi: 10.11896/jsjkx.190900189

• Computer Network • Previous Articles     Next Articles

Cloud Resource Scheduling Mechanism Based on Adaptive Virtual Machine Migration

LI Shuang-gang1, ZHANG Shuang1, WANG Xing-wei2   

  1. 1 College of Software,Northeastern University,Shenyang 110169,China
    2 College of Computer Science and Engineering,Northeastern University,Shenyang 110169,China
  • Received:2019-09-27 Published:2020-09-10
  • About author:LI Shuang-gang,born in 1992,master candidate,is a member of China Computer Federation.His main research interests include mobile social cloud and cloud computing.
    ZHANG Shuang,born in 1971,Ph.D,associate professor,is a member of China Computer Federation.Her main research interests include mobile social cloud and cloud computing.
  • Supported by:
    National Natural Science Foundation of China (61872073, 61572123) and Program for Liaoning Innovative Research Team in University (LT2016007).

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Abstract: Virtual machine (VM) migration is an important research field of current cloud computing resource scheduling.Now the continuous growth of users has brought some new challenges,and current typical migration strategies are difficult to adapt to dynamically changing internal and external environments.Aiming at this problem,this paper proposed an overall framework of adaptive VM migration.Via modeling VM migration,the concepts of “migration path” and “service overhead” were proposed,and the server’s CPU utilization and bandwidth utilization of links between servers were used as indicators to plan the optimal migration path for all to-be-migrated VMs in the system to minimize the total service overhead.Firstly,a threshold-based selection algorithm is presented for the selection of the to-be-migrated VMs.Secondly,an auto regressive integrated moving average model (ARIMA)-based time series prediction algorithm is designed to predict the service overhead within the server’s future time window.Then,the migration path calculation algorithm is designed based on servers’ predicted service overhead and dynamic programming,and an optimal migration plan is made for each to-be-migrated VM.Finally,based on the performance of the prediction window determined by the difference between the predicted service overhead and the real value via the migration path,a prediction window adaptive adjustment algorithm is designed and implemented.Experiments prove that the adaptive VM migration has good effects in terms of adaptive adjustment and minimizing service overhead.

Key words: Adaptive, ARIMA, Dynamic programming, Prediction window, VM migration

CLC Number: 

  • TP302
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