Self-organizing cloud architecture and optimization method and system for edge computing

Abstract

The invention provides a self-organizing cloud architecture and optimization method and system for edge computing. The method comprises: a model construction step: performing model construction on a hierarchical unmanned aerial vehicle system; a decentralized computing unloading algorithm step suitable for an infinite virtual machine resource situation: respectively performing game decision according to conditions met by an unmanned aerial vehicle terminal bandwidth of the unmanned aerial vehicle system so as to achieve Nash equilibrium; and a decentralized computing unloading algorithm step suitable for a finite virtual machine resource situation: designing a decentralized computing unloading algorithm to perform algorithm computing. The invention provides a layered decentralized unloading method to reduce the communication overhead while maintaining the energy efficiency; and according to the self-organizing cloud architecture and optimization method and system provided by the invention, the energy-saving computing unloading decision problem in the hierarchical unmanned aerial vehicle system is modeled as a non-cooperative game for research, the decentralized computing unloadingalgorithm is designed for the situations of infinite virtual machine resources and finite virtual machine resources, and it is proved that the algorithm can achieve the Nash equilibrium.

Description

technical field [0001] The present invention relates to the field of unmanned aerial vehicle system computing offloading, in particular, to an ad hoc cloud architecture and optimization method and system for edge computing. Background technique [0002] At present, as an emerging technology, drones are widely used in military, public security and other fields. With the growth of demand, applications such as target recognition and image processing have gradually emerged, which will generate big data, and it is difficult for a single drone to process such large-scale data. Therefore, an ad hoc cloud system based on multi-UAVs emerged as the times require. In an ad hoc cloud, a large UAV coordinates multiple small UAVs to handle complex events. On the other hand, in many UAV systems, energy consumption is a key issue, and computing offloading, as an important energy reduction technology, has been applied to task offloading between UAVs and cloud servers based on Duoyun. middl...

AI Technical Summary

Problems solved by technology

With the growth of demand, applications such as target recognition and image processing gradually appear, which will generate big data, and it is difficult for a single drone to handle such large-scale data

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