Resource allocation method and device for edge computing terminal, equipment and medium

Abstract

The embodiment of the invention discloses a resource allocation method and device for an edge computing terminal, electronic equipment and a storage medium. The resource allocation method for the edge computing terminal comprises the steps that a daily operation data sample set is acquired; dividing the daily operation data sample set into g-family sample data according to a clustering algorithm; respectively calculating a central processing unit (CPU) resource demand quantity and a random access memory (RAM) resource demand quantity corresponding to each family of sample data; first sample data and second sample data are obtained, resource configuration is carried out according to the first sample data and the second sample data, the first sample data are sample data corresponding to the maximum CPU resource demand quantity in the g-family sample data, and the second sample data are sample data corresponding to the maximum RAM resource demand quantity in the g-family sample data. According to the method, the resource configuration of the CPU and the RAM of each application can be determined, so that the terminal can provide sufficient computing power for the application in each time period, the uncertainty in an operation environment is effectively dealt with, and effective control on the micro-grid is realized.

Description

technical field [0001] Embodiments of the present invention relate to power control technologies, and in particular, to a resource configuration method, apparatus, device, and medium for edge computing terminals. Background technique [0002] Nowadays, people pay more and more attention to the issue of energy conservation, and more renewable energy sources will be connected to the low-voltage distribution network in the form of distributed power sources, prompting the transformation of some low-voltage distribution networks to micro-grids. As a result, the original low-voltage distribution network control system cannot cope with the pressure of concurrent growth of various types of applications such as control and transaction. At present, microservice technology and container technology have been applied in cloud computing, edge computing and power system automation. Microservice technology can split each application into various microservices, avoid repeated development an...

AI Technical Summary

Problems solved by technology

The operating environment of the microgrid is complex, and the application volume of each part of the control system has time-space uncertainty and imbalance

[0003] In order to ensure the reliable operation of the control system, each part of the existing control system adopts a redundant configuration strategy, or even blindly configures it. After the allocation of resources cannot meet the requirements, compensation investment is made, resulting in resource loss and waste.

And in the microgrid control system built by edge computing, the uncertainty of each application makes the time distribution of the computing load of the edge computing terminal uncertain.

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