Cloud host migration method, computer storage medium, and program product

By selecting cloud hosts for migration based on resource usage status and value in cloud computing, and combining the GRU model to predict busy trends, the problem of uneven host resources is solved, load balancing and energy consumption optimization are achieved, and the impact on business is reduced.

WO2026103847A1PCT designated stage Publication Date: 2026-05-21CHINA TELECOM CLOUD TECH CO LTD
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
CHINA TELECOM CLOUD TECH CO LTD
Filing Date
2025-11-14
Publication Date
2026-05-21

AI Technical Summary

Technical Problem

In cloud computing, uneven distribution of host resources can lead to overload of some host machines, affecting the operation of upper-layer applications during cloud host migration. The main issue is how to select cloud hosts for migration to achieve load balancing and resource optimization.

Method used

By obtaining the resource usage status of the host machine and the value of the cloud host, target and non-target hosts are identified. Based on the load data, the business busyness is calculated, and cloud hosts with low value and low busyness are selected for migration. The GRU model is used to predict the business busyness trend, simulate the resource utilization rate after migration, and select a suitable target host for migration.

Benefits of technology

It achieves load balancing and energy saving while reducing the impact of cloud server migration on business operations, avoiding migration failures or business interruptions, and improving resource utilization.

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Abstract

The present application relates to a cloud host migration method, a computer storage medium, and a program product. The method comprises: acquiring the current resource usage states of host machines and the value degrees of cloud hosts on the host machines (step S101); determining a target host machine and a non-target host machine from among the host machines on the basis of the current resource usage states and the value degrees of the cloud hosts (step S102); calculating the service busyness of cloud hosts on the non-target host machine on the basis of load data of the cloud hosts on the non-target host machine (step S103); on the basis of the current resource usage state of the non-target host machine, and the value degrees and the service busyness of the cloud hosts on the non-target host machine, determining, from among the cloud hosts on the non-target host machine, a cloud host to be migrated (step S104); and migrating, to the target host machine, the cloud host to be migrated (step S105).
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