An Energy-Efficient Task Scheduling Mechanism with Switching On/Sleep Mode of Servers in Virtualized Cloud Data Centers

Chunxia Yin, Jian Liu and Shunfu Jin

Mathematical Problems in Engineering, 2020, vol. 2020, 1-11

Abstract:

In recent years, the energy consumption of cloud data centers has continued to increase. A large number of servers run at a low utilization rate, which results in a great waste of power. To save more energy in a cloud data center, we propose an energy-efficient task-scheduling mechanism with switching on/sleep mode of servers in the virtualized cloud data center. The key idea is that when the number of idle VMs reaches a specified threshold, the server with the most idle VMs will be switched to sleep mode after migrating all the running tasks to other servers. From the perspective of the total number of tasks and the number of servers in sleep mode in the system, we establish a two-dimensional Markov chain to analyse the proposed energy-efficient mechanism. By using the method of the matrix-geometric solution, we mathematically estimate the energy consumption and the response performance. Both numerical and simulated experiments show that our proposed energy-efficient mechanism can effectively reduce the energy consumption and guarantee the response performance. Finally, by constructing a cost function, the number of VMs hosted on each server is optimized.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:4176308

DOI: 10.1155/2020/4176308

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