Virtual machine migration method facing green cloud computing

Abstract

The invention discloses a virtual machine migration method facing green cloud computing; the method combines with physics gravitation correlation concepts according to cloud data center server disposition and temperature control mode real conditions, and defines concepts like logic gravitation, correction factor and correction gravitation between physics nodes and the virtual machines; the logic gravitation gathers virtual machines in sequence onto certain data node or data nodes of adjacent areas, thus closing idle nodes; the correction factor can realize virtual machine diffusion on locally heated data nodes, thus stabilizing the system, and preventing node system from collapsing or being damaged; the correction gravitation can preferably gather the virtual machines onto the data node with good thermal diffusivity according to the heat distribution condition and thermal diffusion performance priority strategy in the cloud data center, thus realizing heat distribution balance, and preventing overheating of a frame portion with poor thermal diffusivity; the method can obviously reduce data center energy consumption, can gather the virtual machines, can close partial computing nodes and related refrigeration nodes, thus maximumly saving energy consumption.

Description

technical field [0001] The invention relates to a virtual machine migration method oriented to green cloud computing, in particular to an energy-saving optimization method oriented to cloud computing data center virtual machine management, and belongs to the technical field of cloud computing applications. Background technique [0002] Cloud computing is a computing model that uses the Internet to access shared resource pools (such as computing facilities, storage devices, applications, etc.) anytime, anywhere, on-demand, and conveniently. Resources, which can reduce hardware maintenance costs for small and medium-sized enterprises. At present, the total number of various data centers in my country is about 430,000, which can accommodate about 5 million servers. In the next five years, my country's demand for data center traffic processing capacity will increase by 7 to 10 times. However, the continuous expansion of the scale of cloud data centers and thousands of computing...

AI Technical Summary

Problems solved by technology

There have been a series of research results in the fields of current virtual machine management mechanism and deployment strategy, but these research results generally have some or all of the following problems: 1) Only consider performance, energy consumption, stability, cost, environment, etc. 2) Virtual machine deployment and migration are only performed in units of data nodes, and resources are not integrated in the global scope of the cloud data center. The discreteness of active nodes in the cloud data center leads to regionalization Precision cooling is difficult to implement; 3) Only logically consider the deployment and migration needs of virtual machines, but do not consider the actual physical node deployment scenarios, heat distribution, and actual operation mode of the temperature control system in the cloud data center

Poor linkage between computing equipment and temperature control equipment makes it difficult to apply the results well in the actual environment

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