Device energy consumption control method and apparatus, communication device, and storage medium

By predicting network traffic and controlling energy consumption, the problem of energy consumption differences among different resource types in network devices has been solved, achieving high efficiency and energy saving of equipment and improved service reliability.

CN122120046APending Publication Date: 2026-05-29HUAWEI TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HUAWEI TECH CO LTD
Filing Date
2024-11-27
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing technologies cannot effectively utilize the energy consumption differences of different types of equipment resources in energy-saving operations of network devices, resulting in poor energy-saving effects and insufficient service reliability.

Method used

By acquiring traffic statistics from network devices, traffic data at multiple time granularities can be predicted for future periods. Based on the predicted traffic data at different time granularities, refined energy consumption control can be implemented for device resources of different resource types, including energy saving and wake-up management of devices, chips, and single boards.

Benefits of technology

This approach ensures business operations while fully leveraging the energy-saving capabilities of equipment, reducing energy consumption and minimizing the probability of business disruption.

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Abstract

The application discloses a device energy consumption control method and device, a communication device and a storage medium. In the application, traffic statistical data of a network device is acquired, and predicted traffic data of multiple time granularities of the network device in a future period is acquired based on the traffic statistical data of the network device. On this basis, fine energy consumption control is performed on device resources of different resource types based on the predicted traffic data of different time granularities, so that the device energy saving capability is exerted and the device energy saving effect is improved.
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