Determination method of multi-scale task volume prediction value for cloud computing system

Abstract

The invention provides a cloud-computing-system-oriented multi-scale task quantity predicted value determining method which aims to solve the problem that task quantity prediction precision is difficult to control in a single-scale task quantity prediction method. Long-time tendency, periodic fluctuation and recent situations of the task quantity in a cloud computing system and random perturbation events bursting currently are taken into consideration comprehensively, scientific and reasonable prediction of the user task quantity at a certain moment in the future is carried out, a task quantity prediction level within a period of time in the future is given, and important supporting bases are provided for plans and strategies of cloud service providers in adjustment of resource allocation and the scale of the cloud computing system.

Description

technical field [0001] The present invention relates to a cloud computing system, in order to improve the cloud computing system's ability to respond to future tasks, and can adopt a multi-scale task amount prediction value determination method. The technology belongs to the cross-technical application field of computer network, computer software and distributed computing. Background technique [0002] With the current increasingly fierce market competition and globalization, cloud computing service providers need to adopt more advanced and efficient management and operation methods for the management and use of computing, storage and information resources in its cloud computing platform. [0003] The important indicators of the responsiveness of cloud computing refer to the response speed and prediction accuracy of cloud computing to future tasks. Prediction is to predict and infer unknown events based on the regularity of known events, including speculation on events that...

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Problems solved by technology

[0005] Technical problem: The purpose of this invention is to propose a method for determining the multi-scale task volume prediction value for cloud computing systems, aiming at the problem that the task volume prediction accuracy is difficult to control caused by the current single-scale task volume prediction method, from the macro and micro perspectives Multidimensional factors to make more scientific and reasonable predictions on the amount of tasks submitted by users in the future, so as to effectively support the resource allocation decisions of cloud service providers and ensure the normal operation of cloud computing systems

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