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

Abstract

The present invention relates to the field of mobile edge computing, in particular to a user terminal task offloading method of an edge computing service system, comprising steps: a local edge node receives a task offloading request from a local terminal, obtains computing resource usage information of itself and adjacent edge nodes, and according to the task The required resource situation, and the current available edge node resource usage, adopt the local resource priority strategy based on the resource threshold, select the local edge node, the adjacent edge node or the computing node of the cloud computing center to perform the task; the local edge node sends the selected The edge node or computing node requests confirmation and execution of the task; the edge node or computing node carrying the task returns the task execution result to the terminal, and sends the task execution record to the cloud computing center. In the present invention, the offloading task allocation is decided by the local edge nodes, and the rationality and balance of resource usage among the edge computing nodes are optimized under the condition of ensuring user experience quality and service quality.

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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