Resource management method of data center based on statistic model in cloud computing environment

Abstract

The invention relates to a resource management method cluster of a data center based on the statistics in cloud computing environment, which comprises four steps of: 1. collecting work loads, application problem performance and resource use condition information; 2. inputting the information into a model and carrying out model analysis by using a statistic analysis method KCCA (Kernel Canonical Correlation Analysis) and remote-distance relative algorithm; 3. classifying work modes according to the current environment, and regulating the resource distribution according to control parameters; and 4. regulating the resource distribution according to the controller output and simultaneously updating the resource states. The resource management method of the invention firstly considers the characteristic that the work loads of the novel data center in the cloud computing environment are continuously changed, the real-time monitoring and the elastic management are carried out on the resources of the data center according to user requirements and the resource use conditions to ensure that the integral resource consumption can reach the minimum under the condition that the system performance is not influenced. The resource management method has wide practical value and application prospects in the technical field of elastic resource management of the cloud computing data center.

Description

(1) Technical field [0001] The present invention relates to a resource management method using a statistical learning model and machine learning for a new type of data center in a cloud computing environment, in particular to a resource management method based on a statistical model for a data center in a cloud computing environment, which manages load and resource allocation online , to improve system performance, belonging to the field of cloud computing elastic resource management. (2) Background technology [0002] At present, with the rapid development of network applications, the demand for computing power continues to increase, and the number of existing data center servers continues to increase. How to manage a huge server cluster has become the focus of everyone's attention. With the popularity of cloud computing, more and more network (Web) services and business applications are deployed in the cloud computing environment. For the massive servers in the cloud compu...

AI Technical Summary

Problems solved by technology

The data collected in this way cannot represent the overall data in the production operating environment, and cannot handle the changing workload in the cloud computing environment

This method is inflexible in the management of resources, and cannot dynamically adjust resources and performance according to the actual needs of data center users, and may cause a significant drop in system performance when workloads surge

Images