Resource adjustment method and device of edge computing node, equipment and medium

By monitoring the resource usage and business scenario data of edge computing nodes and dynamically adjusting resource allocation, the problem of uneven resource allocation in the existing technology is solved, and the system's response speed and stability are improved.

CN119645618APending Publication Date: 2025-03-18CHINA TELECOM ARTIFICIAL INTELLIGENCE TECHNOLOGY (BEIJING) CO LTD
0 Cites 7 Cited by

Patent Information

Application Number
CN202411472215.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-21
Publication Date
2025-03-18

AI Technical Summary

Technical Problem

The prior art lacks flexibility in resource allocation of edge computing nodes, and it is difficult to adapt to changes in different business scenarios and resource conditions, resulting in uneven resource allocation, high response delay and poor system stability.

Method used

By monitoring the target resource usage and business scenario data of edge computing nodes, dynamically select appropriate scheduling policies from the pre-established scheduling policy database, and adjust the resource allocation of each edge computing node.

Benefits of technology

It realizes dynamic adjustment of edge computing node resources allocation according to different business scenarios and resource conditions, improves resource utilization efficiency, reduces response delay, and enhances system stability.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention provides a resource adjustment method and device for edge computing nodes, equipment and a medium, and belongs to the technical field of computers.The method comprises the steps that the use condition and service scene data of target resources associated with all the edge computing nodes are monitored, the target resource comprises at least one of a central processing unit (CPU), a memory and a network bandwidth; according to the monitored data, a target scheduling strategy is selected from a pre-established scheduling strategy library, and the scheduling strategy library comprises resource scheduling strategies for different service scenes and resource use conditions; and according to the target scheduling strategy and the current use condition of the target resource by each edge computing node, adjusting the resource currently allocated to each edge computing node.
Need to check novelty before this filing date? Find Prior Art