Resource reservation method, resource allocation method, device, storage medium and program product

By reserving cloud resources from multiple clients into a shared reserved resource pool and using historical information to predict usage, the problem of idle cloud resources and declining sales rates has been solved, achieving efficient resource utilization and cost savings.

CN122450641APending Publication Date: 2026-07-24ALIBABA CLOUD COMPUTING CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ALIBABA CLOUD COMPUTING CO LTD
Filing Date
2025-01-24
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

When cloud providers experience a sudden surge in user demand for resources, other users may not be able to obtain sufficient resources. Furthermore, users' failure to fulfill or fully fulfill their obligations may lead to idle cloud resources, reducing utilization and resource sales rates, and increasing costs.

Method used

Cloud resources from multiple clients are reserved in a shared reserved resource pool. By learning from historical information, the overall usage is predicted, the amount of resources reserved is reasonably determined, and resources are transferred from the public resource pool to the reserved pool for reuse, thus eliminating resource binding relationships.

Benefits of technology

It improved the utilization rate of cloud resources, increased the sales rate of resources, reduced the reservation cost, and enabled flexible management and efficient use of resources.

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Abstract

Embodiments of the present application provide a resource reservation method and a resource allocation method, a device, a storage medium and a program product. In the embodiments of the present application, cloud resources reserved for multiple clients are unified into a reserved resource pool, and the reserved resource pool is shared by the multiple clients, so that the binding relationship between the cloud resources and the clients can be eliminated, the reserved cloud resources in the reserved resource pool can be reused by the multiple clients, the utilization rate of the cloud resources is improved, and the resource selling rate of a cloud vendor is improved. In the resource reservation, the overall use condition information of the current cloud resource reservation is reasonably predicted by learning the historical information related to the cloud resource reservation of the multiple clients, and the overall resource reservation quantity of each resource specification is determined in combination with the resource specification and the resource quantity of the cloud resources reserved by the multiple clients, so that the reserved resource quantity can be saved, and the resource reservation cost is reduced.
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