A dynamic resource monitoring and scheduling method of cloud computing platform iaas layer

Abstract

The invention provides a dynamic resource monitoring and scheduling method of the IaaS layer of a cloud computing platform, relates to the technical field of cloud computing, and is used for monitoring and scheduling the resources of a data center composed of a control server and several computing servers, including the control server collecting data center resources The current status information of each computing server; traverse and collect the usage status of all working nodes in the data center; judge the load status of the working nodes in the data center; judge the virtual machine migration conditions; select the target virtual machine in the working node to be migrated; The target virtual machine selects the target server; the target virtual machine is migrated to the determined target server; the present invention uses the time-based SLA comprehensive level to measure the computing power of each server in the data center, and uses the size of memory and bandwidth as considerations for resource scheduling. Complete the resource scheduling of heterogeneous data centers. According to the memory usage of all virtual machines, the scheduling cost of each virtual machine is effectively measured by using range segmentation.

Description

technical field [0001] The invention relates to the technical field of cloud computing, in particular to a dynamic resource monitoring and scheduling method of the IaaS layer of a cloud computing platform. Background technique [0002] With the rapid development of cloud computing technology, the various resources of the data center in the cloud environment are also increasing. How to reduce the energy consumption of the data center through resource scheduling and improve the utilization of system resources is a very important content. . At present, resource scheduling methods aimed at reducing data center energy consumption mainly include two types of methods: the first type mainly achieves energy saving by dynamically adjusting the voltage or frequency of the CPU; the second type is to shut down unnecessary servers resources to achieve energy saving. At present, the main strategy adopted by the scheduling method aimed at improving the utilization rate of system resources...

AI Technical Summary

Problems solved by technology

However, the reality is that the server configurations in the data center are often different, so the effect of the scheduling method is not ideal

This method only considers the computing power of the server, and does not fully consider the memory and network resources

At the same time, this scheduling method does not take into account the overall impact of scheduling costs and scheduling time on scheduling

Finally, this method does not take into account the impact of the server's instantaneous load change on resource scheduling, so it is prone to instantaneous load peaks or valleys to trigger unnecessary scheduling, resulting in waste of resources and affecting overall performance.

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