Hopfield neural network-based server energy-saving method and device for cloud data center

Abstract

The invention discloses a Hopfield neural network-based server energy-saving device for a cloud data center. The device comprises a data storage part, a control part and an energy-saving strategy training part, wherein the data storage part is used for storing monitoring data and energy-saving strategy information of a server group; the control part is responsible for service control, wherein the service control comprises generation and acquisition of the monitoring data, and matching and implementation of an energy-saving strategy; the energy-saving strategy training part is used for training a Hopfield neural network based on the monitoring data to generate the energy-saving strategy information. The invention also discloses a corresponding method. According to the device and the method, the problems that most energy-saving strategies are single in setting and are not accurate and reasonable enough, and the energy consumption of the data center cannot be adjusted very well are effectively solved.

Description

technical field [0001] The invention relates to a management and monitoring module in a cloud computing operating system, in particular to a server energy-saving method and device based on a Hopfield neural network in a cloud data center. Background technique [0002] According to Wikipedia's definition, cloud computing (Cloud Computing) is an Internet-based computing method in which shared hardware and software resources and information can be provided to computers and other devices on demand. [0003] Cloud computing is another sea change following the great shift from mainframe computers to client-server in the 1980s. Users no longer need to know the details of the infrastructure in the "cloud", have corresponding professional knowledge, and do not need to directly control it. Cloud computing describes a new Internet-based IT service growth, consumption and delivery model, usually involving the provision of dynamically scalable and often virtualized resources over the In...

AI Technical Summary

Problems solved by technology

In a large-scale cloud data center built on the basis of a cloud computing operating system, the number of devices is huge, and the monitoring and management process is complex. How to effectively realize the high efficiency and energy saving of the cloud data center is a problem worth studying.

[0005] At present, most energy-saving strategies only consider temperature trigger or power trigger when setting, and do not comprehensively analyze and consider the real-time load information of the server, such as CPU, memory, network bandwidth, and disk IO. OK, the overall power consumption of the system is too high

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