Mobile edge computing method, device and system for internet of things

Abstract

The invention provides a mobile edge calculation method, device and system for the Internet of Things, and the method comprises the steps: distributing unmanned aerial vehicles for all Internet of Things equipment based on the current simulation positions of all unmanned aerial vehicles and the actual positions of all Internet of Things equipment in a target Internet of Things region; simulating to unload the tasks of the Internet of Things equipment to the distributed unmanned aerial vehicles, and simulating each unmanned aerial vehicle to schedule the received tasks based on a deep reinforcement learning algorithm; using a differential evolution algorithm to iteratively update the current simulation position of each unmanned aerial vehicle, continuing to execute the above operation, andstopping the operation until the number of times of iterative update reaches a preset threshold; determining the optimal coordinate position of each unmanned aerial vehicle based on the unmanned aerial vehicle allocated by the Internet of Things equipment in each operation, a task scheduling result of the unmanned aerial vehicle and the current simulation position of the unmanned aerial vehicle; and triggering each unmanned aerial vehicle to move to the optimal coordinate position to schedule the task on the corresponding Internet of Things device. According to the invention, the service quality of the Internet of Things equipment is improved.

Description

technical field [0001] The present invention relates to the technical field of the Internet of Things, in particular to a mobile edge computing method, device and system for the Internet of Things. Background technique [0002] Due to the limited energy and computing power of IoT devices, IoT devices cannot handle complex services. The current technology of using UAVs to optimize the performance of communication systems mainly includes two methods: one is to use UAVs as air relays, and ground IoT devices transmit collected data to UAVs in the air, through one or more An aerial UAV acts as a relay node to transmit data to the target data center, and IoT devices can also download data through the UAV as a relay node instead of directly downloading data from the data center; the other is to use wireless As a base station in the air, the man-machine uses drones to enhance the communication performance of the coverage area and improve the throughput of the network. However, the...

AI Technical Summary

Problems solved by technology

However, the existing unmanned aerial vehicle optimization communication system performance technology does not solve the problem of low computing resources of the IoT device itself, resulting in the existence of low service quality due to the low computing resources of the existing IoT devices. question

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