Virtual machine placement method based on artificial bee colony algorithm

Abstract

The invention discloses a virtual machine placement method based on an artificial bee colony algorithm; the method comprises the steps: collecting the remaining resource information of all physical machines in a cloud platform after receiving a request for newly building a virtual machine, and classifying the physical machines according to the remaining resource conditions of the physical machines; then comprehensively considering two resource dimensions of a CPU (Central Processing Unit) and a memory, aiming at reducing resource fragments and the number of active physical machines, and discretizing a continuous artificial bee colony algorithm so as to solve a virtual machine placement problem; introducing a physical machine and a to-be-placed virtual machine into the artificial bee colony algorithm, wherein in the placing process, the employed bees update the nectar source according to the physical machine resource balance degree, and the scout bees randomly find a new nectar source. According to the method, the resource fragments of the cloud platform are optimized, the virtual machine is placed, the resource fragments in the cloud platform are reduced, and the resource utilization rate of the cloud platform is improved on the premise of ensuring low power consumption.

Description

technical field [0001] The invention relates to the technical field of cloud computing, in particular to a virtual machine placement method based on an artificial bee colony algorithm. Background technique [0002] At the end of 2018, the number of data center racks owned by my country has increased significantly, and there are about 2.262 million data center racks of various sizes. In the whole year of 2020, 2.7% of the power generation of the whole society in my country is used for data centers. Due to the commissioning of data centers The number is steadily increasing, and data center electricity consumption will increase further. The energy consumption of all physical machines contained in the data center accounts for 80% of the total energy consumption of the data center hardware equipment. As far as a single physical machine is concerned, the power consumption of a physical machine that is powered on and has no load or a very low load can reach the peak energy consumpti...

AI Technical Summary

Problems solved by technology

[0003] Many literatures have studied how to improve data center resource utilization efficiency through virtual machine placement methods, but there are the following deficiencies: the reduction of resource fragmentation of physical machines is not considered as an optimization goal, and it is difficult to improve the resource utilization efficiency of physical machines, resulting in waste of energy consumption

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