Industrial field big data task coordination degree method based on edge calculation

Abstract

The invention discloses an industrial field big data task coordination degree method based on edge calculation. The method comprises the steps: S1, enabling a scheduler to obtain a task amount Ni and a time delay Ti; S2, evaluating the priority of each task; S3, obtaining the network residual bandwidth R and the uploading rate Li of the tasks, wherein Li represents the uploading rate of the ith task, task queuing waiting is carried out according to the priority, and delay Wi is recorded; S4, obtaining a task scheduling threshold alpha of the scheduler, calculation information of each edge server, the number l of task queuing processing and queuing waiting delay; and S5, carrying out cooperative scheduling on the tasks according to a system resource state, a current business task amount and a delay requirement. According to the invention, resource scheduling of the task between the terminal and the edge server is realized through edge computing, reasonable scheduling of the industrial field task between the terminal equipment and the edge server is achieved, computing resources of the system are fully considered, the task processing capability of the system is improved, the resource consumption of the system can be minimized, and the real-time performance of task scheduling is improved.

Description

technical field [0001] The invention relates to the field of big data technology, in particular to a method for coordinating large data tasks in industrial sites based on edge computing. Background technique [0002] With the rapid development of industrial Internet and mobile communication technology, applications such as face recognition, short video traffic, automatic driving, drone operation, and industrial inspection have put forward higher demands on the amount of computing, relying only on the current centralized cloud computing architecture It is not enough for the model to provide business computing capabilities. There is an urgent need to expand the cloud-centric computing architecture to the distributed computing service architecture, and the most representative models are edge computing and fog computing. [0003] With the generation of big data, the computing power of mobile terminals has also begun to rise. According to the type of data and service quality req...

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Problems solved by technology

[0006] Aiming at the low real-time performance of collaborative scheduling of industrial field big data tasks in the prior art, the present invention proposes a method for coordination degree of industrial field big data tasks based on edge computing. Scheduling, in the case of minimum resources, can also ensure user satisfaction, so as to meet the real-time task processing generated in various industrial production processes

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