Air-ground collaborative edge calculation method and system

Abstract

The invention discloses an air-ground collaborative edge calculation method and system. The air-ground collaborative edge calculation method specifically comprises the following steps: setting initialization information; in response to the completion of the initialization parameters, performing distribution of calculation tasks; in response to completion of allocation of the calculation task, performing allocation of communication resources; in response to completion of communication resource allocation, performing allocation of computing resources; determining the trajectory of the unmanned aerial vehicle in response to the completion of the allocation of the computing resources; in response to completion of trajectory determination of the unmanned aerial vehicle, determining a duration value; in response to the determination of the completion duration value, updating the calculation efficiency; judging whether the calculation efficiency meets preset convergence precision or not; and if yes, outputting the allocation result of the communication resources, the allocation result of the computing resources, the track of the unmanned aerial vehicle and the duration value as optimal results. According to the invention, the purposes of system resource allocation including communication resources and computing resources and combined unmanned aerial vehicle flight path design are achieved.

Description

technical field [0001] The present application relates to the field of big data, and in particular, relates to an air-ground collaborative edge computing method and system thereof. Background technique [0002] With the rise of the Internet of Things, the number of different types of TDs (Terminal Devices, Terminal Devices) such as cloud sensors, smartphones, and wearable devices is increasing rapidly; intelligent applications such as face recognition, interactive games, and virtual reality are also emerging. However, due to the weak computing power and low battery capacity of these end devices, efficiently computing the massive computational data generated by these applications is a thorny issue. In this context, MEC (Mobile Edge Computing, Mobile Edge Computing), as a technology with great development potential, can help TDs perform data processing and computing at the edge of the network (such as access points and base stations), so that the above problems can be solved. ...

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