Mobile user terminal task unloading method under distributed edge computing service system

Abstract

The invention relates to the field of mobile edge calculation and particularly relates to a user terminal task unloading method of an edge computing service system. The method comprises the followingsteps that: a local edge node receives a task unloading request of a local terminal, acquires computing resource use information of the local edge node, and adopts a local resource priority strategy based on a resource threshold according to a resource condition required by the task and a resource use condition of the currently available edge node; the local edge node requests confirmation from the selected edge node or a computing node and executes the task; and the edge node or the computing node bearing the task returns a task execution result to the terminal, and sends a task execution record to the cloud computing center. According to the method, the local edge nodes decide to unload task allocation, and the rationality and balance of resource use among the edge computing nodes are optimized under the condition that the user experience quality and the service quality are guaranteed.

Description

technical field [0001] The invention relates to the field of mobile edge computing, in particular to a user terminal task offloading method of an edge computing service system. Background technique [0002] With the rapid development of the mobile Internet, mobile user devices continue to proliferate, such as smartphones, tablet computers, smart homes, and IOT devices. The application scenarios of these devices are becoming more and more abundant, resulting in many computing-intensive usage scenarios, such as VR, AR, and intelligent recognition. However, due to its portability, mobile user equipment is restricted by computing power and battery life. With the development of cloud computing technology, cloud computing capabilities are used to give mobile devices more powerful computing power to meet application needs. However, the general cloud computing cluster is far away from the mobile user equipment, resulting in a large communication delay. It is difficult for these c...

AI Technical Summary

Problems solved by technology

If the task placement decision is made by the remote cloud computing center, it will not only bring about the reliability problem of single point of failure, but also greatly increase the decision-making delay because the decision-making center is far away from the mobile user equipment.

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