Docker and virtual machine aggregation placement method based on multi-objective biogeography optimization algorithm

Abstract

A Docker and virtual machine aggregation placement method based on multi-objective biogeography optimization algorithm includes that firstly, Creatively Docker and virtual machine are taken as a unitof aggregation to build a DVMP (Docker and Virtual Machine Placement, Docker and VM placement) constraint model based on DVP three-tier architecture; Secondly, the constraint conditions of DVMP constraint model are defined, and the DVMP aggregation placement model is established. Next, a mapping method of MBBO-based Docker and virtual machine aggregation placement is executed; Then, the convergence scenario is adapted and coded to obtain the effective solution, and the optimal solution of the convergence problem between Docker and virtual machine is found by iteratively updating the initial population. Finally, Docker and virtual machine are aggregated according to the optimal placement scheme. The method of the invention can solve the problem that the virtual machine resource occupies large amount and is difficult to aggregate, and can optimize the energy consumption of the data center and the utilization rate of the server resource.

Description

technical field [0001] The invention belongs to the field of virtual machine aggregation in cloud computing, and specifically relates to a multi-objective biogeographical optimization algorithm-based aggregation placement method for Docker and virtual machines, which is used to use Docker and virtual machines as aggregation units at the same time to solve virtual machine resource occupation For problems that are too large to be further aggregated, the algorithm adopted can avoid falling into local optimum, and greatly optimize the energy consumption of the data center and the resource utilization of the server. Background technique [0002] Since 2008, cloud computing (Cloud Computing) technology has developed rapidly, and data centers have expanded rapidly, which has brought serious energy consumption and high operating costs. Existing studies have shown that data center energy consumption is closely related to the resource utilization rate of physical servers. Therefore, i...

AI Technical Summary

Problems solved by technology

The invention creatively uses Docker and a virtual machine as an aggregation unit at the same time to solve the problem that virtual machine resources occupy a large amount and are difficult to further aggregate; the algorithm adopted can avoid falling into a local optimum, and greatly optimize the energy consumption of the data center and the resource utilization rate of the server

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