Task processing method, device and system in cloud computing platform

Abstract

The invention discloses a task processing method in a cloud computing platform, the method comprising generating a predetermined number of first scheduling schemes according to scheme generation information sent by a user; conducting iterative processing on the first scheduling schemes based on a multi-scale quantum harmonic oscillator algorithm to obtain a predetermined number of current scheduling schemes; calculating the energy consumption of each current scheduling scheme, and selecting the lowest energy consumption scheduling scheme; processing the tasks in the cloud computing platform according to the lowest energy consumption scheduling scheme. While guaranteeing the computing ability of the cloud computing platform, this method is based on the multi-scale quantum harmonic oscillator algorithm to optimize a predetermined number of scheduling schemes and obtain the lowest energy consumption scheduling scheme, effectively ensuring the cloud computing platform to play a high-performance and low-energy consumption strength enabling the performance of the platform to be fully exerted. The invention also discloses a task processing device and system and a computer-readable storagemedium in a cloud computing platform, all of which have the above beneficial effects.

Description

technical field [0001] The present application relates to the technical field of cloud computing, in particular to a task processing method in a cloud computing platform, and also relates to a task processing device, system and computer-readable storage medium in a cloud computing platform. Background technique [0002] As a new type of computing, cloud computing has quickly become a research hotspot in academia and industry due to its advantages of high scalability and high availability. Faced with many challenges, high energy consumption is one of the most serious problems in cloud computing systems. [0003] In the cloud computing system, in addition to the necessary energy consumption generated when processing tasks, there is also a waste of energy consumption during its operation. First of all, due to the randomness of the arrival of computing tasks, the amount of tasks arriving per unit time is sometimes sparse and sometimes dense. However, the existing cloud computin...

AI Technical Summary

Problems solved by technology

However, although the Min-min algorithm guarantees the shortest task processing time, it will cause the resource nodes with strong processing capabilities to be in the working state all the time, while other resource nodes are always in the idle state, which cannot reflect the advantages of distributed processing; , since resource nodes with strong processing capacity are always in working state, this will cause rapid loss of resource nodes with strong processing capacity

In summary, since the Min-min algorithm only focuses on the completion time of the task, without considering other factors such as energy consumption, it causes problems such as extremely large average power and serious power consumption on the cloud computing platform.

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