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Workload Prediction-based Algorithm for Consolidation of Virtual Machines |
Wei Liang Huang Tao Chen Jian-ya Liu Yun-jie |
Key Laboratory of Universal Wireless Communications of Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
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Abstract For issue of Virtual Machine (VM) migration in cloud computing environment when it comes to meeting the demands of load balancing, auto scaling, green energy-saving, etc. This paper design a scheduling algorithm that is cloud computing infrastructures oriented and workload prediction based. By organically integrating the active control technology based on workload prediction and the passive control technology based on status information of actual system, as well as with the exponential smoothing prediction model to predict the workload condition in future time, a VM consolidation algorithm is put forward which takes the maximum future workload as first in the VM selection stage and compares the resource demand queues in the VM placement stage. The simulation results show that the algorithm uses the prediction-based resource integration to reduce the number of servers and virtual machine migrations as well as service level agreement violations, effectively increasing the overall resource utilization of data center as the core of the cloud infrastructure.
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Received: 03 September 2012
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Corresponding Authors:
Huang Tao
E-mail: htao@bupt.edu.cn
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