Cloud computing server cluster resource allocation control system and method

Abstract

The invention provides a cloud computing server cluster resource allocation control system and method: the initial matching optimization module analyzes the matching degree of the task feature vector of the analysis operation task and the resource allocation vector of the resource allocation mode, and determines the resource allocation mode of the analysis operation task; dynamic optimization The module conducts dynamic optimization during the execution of the subtasks included in the analysis and calculation tasks; the task scene judgment module judges that there is a dynamicity caused by the subtask execution itself or external disturbances that cause the matching optimization of the initial matching optimization module to fail, and then enters the re-matching The optimization module restarts the execution process of the subtask through the dynamic optimization module; the matching optimization module analyzes the matching degree between the task feature vector of the analysis operation task and the resource allocation vector of the resource allocation mode, determines the resource allocation mode of the analysis operation task, and realizes the server cluster Matching optimization for resource allocation. It can take into account resource optimization and matching, adapt to dynamics, and can suppress the phenomenon of too frequent resource allocation.

Description

technical field [0001] The invention relates to the technical field of resource allocation, in particular to a cloud computing server cluster resource allocation control system and method. Background technique [0002] In order to meet the actual needs of big data, artificial intelligence and other aspects of analysis and computing, cloud computing technology has developed rapidly in recent years. Cloud computing uses the server cluster located in the cloud as the execution carrier of the analysis operation. The server cluster obtains the analysis operation task submitted by the client through the network, executes the calculation in response to the demand of the analysis operation task, and feeds back the calculation execution of the analysis operation task to the client. result. Cloud computing takes advantage of the scale advantages and centralized management advantages of cloud server clusters, which can undertake massive, high-concurrency and resource-intensive operati...

AI Technical Summary

Problems solved by technology

[0003] At present, in the prior art, the server clusters in the cloud are used to perform calculations in response to the requirements of the analysis and calculation tasks, and there is a lack of solutions that can take into account resource optimization and matching, adapting to dynamics, and suppressing excessive resource allocation.

Images