A cloud computing optimization method, system and medium that integrates and restricts periodic quasi-dormant

Abstract

The invention discloses a cloud computing optimization method that integrates and restricts periodic quasi-dormant, which includes the following steps: obtaining the average response time T of unloading cloud tasks to a cloud server to receive services C , the average response time T of the cloud task receiving service from the local processor MD And the average response time T of the cloud task, according to the average power consumption of the cloud task receiving service on the i-th physical machine in the cloud and the average power E of the cloud system to construct a system optimization function F, to obtain the optimal combination of cloud task unloading probability and adopt the proposed method of the present invention The cloud computing optimization method, setting reasonable parameters for the cloud computing energy saving strategy, can reduce the energy consumption level of the cloud system and ensure the service quality of the cloud task at the same time.

Description

technical field [0001] The invention relates to the technical field of cloud computing and task offloading, and in particular to a cloud computing optimization method that integrates and limits periodic quasi-dormant, a cloud computing optimization system and a readable storage medium thereof. Background technique [0002] At present, the operation method of data center network in the cloud environment is becoming more and more flexible, while the traditional data center can no longer meet these requirements. The difference between cloud data center and traditional data center lies in high virtualization, automatic management and green energy saving. Generally, cloud data centers include two energy-saving strategies: energy reduction and power management. The strategy of reducing energy consumption mainly starts with reducing idle energy consumption and operating energy consumption. Power management strategies can be divided into dynamic power management and static power m...

AI Technical Summary

Problems solved by technology

However, in the sleep mechanism in these studies, the virtual machine in the sleep state does not work at all. Although the energy consumption of the cloud system is effectively reduced, the service quality of the cloud task cannot be guaranteed.

So far, research on cloud computing energy-saving strategies that introduce semi-dormancy mechanisms is very scarce.

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