Abstract
In accordance with the dynamically changing characteristics of user application load demand, the optimization of energy consumption in the process of virtual machine automatic deployment on the basis of the effective integration of user personalized resource demand in cloud platforms and the dynamic migration technology of virtual machines is studied in this work. Aiming at the problem of energy consumption optimization, an energy-efficient virtual machine deployment framework, which can be dynamically adjusted in accordance with the user’s actual resource needs, is designed. In the virtual machine deployment framework, this paper presents a virtual machine deployment selection algorithm based on a double-cursor control mechanism for the resource usage state of CPU and memory, which achieves a binocular optimization balance to a certain extent. Simulation experiment results show that when the virtual machine deployment framework proposed in this paper and the virtual machine deployment selection algorithm based on a double-cursor control mechanism are combined, the number of necessary active physical nodes in the cloud data center can be effectively controlled, and the frequency of virtual machine migration synchronization can be reduced. Consequently, the cloud data center can maintain low energy costs.
Highlights
To some extent, cloud computing [1,2] is an effective extension of traditional parallel, distributed, grid, and edge computing
The virtual machine resource allocation model [2], which is based on user benefit maximization and the virtual machine deployment mechanism of cloud platforms, has a critical effect on effective resource utilization and energy consumption
In accordance with the personalized adjustment of user resources, this paper mainly considers the effects of CPU and memory on physical resource utilization, host energy consumption, virtual machine migration, and servicelevel agreement (SLA) violations and proposes a virtual machine deployment scheme based on a double-cursor control mechanism with balanced performance and energy consumption
Summary
Cloud computing [1,2] is an effective extension of traditional parallel, distributed, grid, and edge computing. First, we formulate our optimization problem as a 2D optimization problem based on a double-cursor control mechanism for the resource usage state of CPU and memory. This method is different from the traditional way. This study proposes a framework for the dynamic deployment of virtual machines and presents a virtual machine deployment selection algorithm based on the double-cursor control mechanism for the resource usage state of CPU and memory, which achieves a binocular optimization balance.
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