Edge computing task unloading method for industrial internet of things

Abstract

The invention relates to an edge computing task unloading method for the industrial internet of things. The method comprises the following steps: constructing a three-layer edge computing node networkmodel; planning a point-to-point optimal path in the network through an SDN (Software Defined Network) controller; defining a time delay model from an equipment unloading task to each layer of edge computing nodes, and selecting N better edge computing nodes as candidate nodes for task unloading through a primary selection rule in the edge computing nodes of which the total time delay of the computing equipment task is less than the maximum tolerable time delay of the task; and taking the length and priority of the equipment task and the ratio of the transmission delay of task unloading to the maximum tolerable delay of the task as fuzzy logic input variables, and selecting an optimal node in the candidate nodes by adopting a fuzzy logic algorithm to unload the task. By means of the taskunloading method, the difference requirements of the equipment for data real-time performance and computing resources are guaranteed, and the transmission and processing time of equipment tasks is shortened.

Description

technical field [0001] The invention belongs to the field of edge computing, and relates to an edge computing task offloading method for industrial internet of things. Background technique [0002] Edge computing is an open platform that integrates core capabilities such as network, computing, and storage at the edge of the network close to the source of objects or data to meet the needs of rapid interactive response and provide universal and flexible computing services. Task offloading in edge computing is to offload the computing tasks of the device terminal to the edge computing environment at the edge of the network, so as to solve the problems of terminal devices in terms of computing resources, storage space, and energy efficiency. [0003] In the industrial Internet of Things environment, the traditional cloud computing service adopts a centralized processing method, which has the advantages of low cost, high reliability and scalability, but there are also problems su...

AI Technical Summary

Problems solved by technology

With the continuous improvement of the real-time data requirements of the bottom equipment of the modern factory and the differential requirements for computing resources, cloud computing services have been difficult to meet some production environments that require high real-time data. The emergence of edge computing has effectively made up for this. There are some deficiencies in cloud computing. At this stage, most of them adopt the unloading method of single-layer edge computing nodes, which effectively solves the real-time demand of data, but ignores the different requirements of computing resources for different underlying equipment tasks in the factory, making computing resources are not fully utilized

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