Dynamic Consolidation Based on Kth-Order Markov Model for Virtual Machines

  • Na JiangEmail author
Conference paper
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)


The rapid development of cloud computing technology has led to a high level of energy consumption. The central processing unit (CPU) of the data center and other resources often use less than half the rate; therefore, if the work of the virtual machine is focused on part of the server, and the idle server switches to low power mode, the power consumption of the data center can be greatly reduced. Traditional research into virtual machine consolidation is mainly based on the high load threshold of the current host load setting or periodically migrates, and the present study made predictions based on the timing of problems of lower prediction accuracy faced. To solve these problems, we consider the impact of the multi-order Markov model and the CPU state at different times, and propose a new hybrid sequence K Markov model for the next period of time of the host CPU load forecasting. Owing to the large-scale data experiment on the CloudSim simulation platform, the host load forecasting method proposed in this paper is compared with the traditional load detection method to verify that the proposed model has a large reduction in the number of virtual machine migrations and amount of data center energy consumption, and the violation of the service level agreement (SLA) is also at an acceptable level.


Cloud computing Dynamic virtual machine integration Hybrid Markov model 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Zhaotong UniversityZhaotongChina

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