Resource dynamic pricing method in edge calculation

Abstract

A resource dynamic pricing method in edge computing comprises the steps of firstly sending a task processing request to a base station by a user, judging whether unloading is needed by the base station according to the request, and if yes, further uploading a task to an edge cloud server by the user; otherwise, completing task processing by the user himself / herself; then judging the computing resource remaining condition of the edge cloud server, and if the resource remaining amount is higher than half of the total resource amount and the user demand is not strong, adjusting the resource priceto a lower level; if the resource margin is lower than half of the total amount and the user demand is strong, adjusting the resource price to a higher level; and determining the size of the unloading task according to the resource price by the user, and jointly completing calculation task processing by the user and the edge cloud server. The edge cloud server provided by the invention has betterresources, and can meet the user demands in a large probability through effective resource pricing distribution, thereby optimizing the edge cloud and user income.

Description

technical field [0001] The present invention relates to the technical field of mobile edge computing, relates to a computing offloading strategy, and in particular to a resource dynamic pricing method based on the Stackelberg game. Background technique [0002] With the continuous development of mobile networks and Internet of Things technologies, a large number of mobile devices are connected to the Internet, and global mobile data traffic has doubled. The traditional cloud-end processing method has gradually encountered problems such as load bottlenecks and large transmission delays. At the same time, long-distance data transmission occupies a large amount of network bandwidth. For terminal devices with limited battery life and computing resources, it is difficult to satisfy computing-intensive Applications with high demands on communication. [0003] In order to meet the above challenges, the concept of Mobile Edge Computing (MEC) is proposed. Mobile edge computing is a...

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Problems solved by technology

[0004] During the implementation of the present invention, the inventors found that the prior art has the following deficiencies: In the existing mobile edge computing network scenarios, most of the research work did not take into account the limited computing resources of the MEC server and the relationship between system resources and user needs. connection between

However, compared with mobile terminals, although MEC servers have more resources, they are actually still very limited. The method of allocating resources to users in a unified pricing manner will cause waste of limited resources. Therefore, in limited resource management solutions Need to further explore effective resource allocation methods in

In the existing research work, the vast majority of documents focus on the user side or the edge cloud side as a single optimization goal. In the architecture design of the future mobile communication system, through the collaborative computing between the user and the edge cloud, it is necessary to deeply optimize the entire system. Performance, this kind of modeling object that only considers one side is not comprehensive

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