Cloud collaborative multi-task scheduling method and device

Abstract

An embodiment of the invention provides a cloud collaborative multi-task scheduling method and a cloud collaborative multi-task scheduling device. The cloud collaborative multi-task scheduling methodcomprises the steps of: acquiring a to-be-processed task received by each edge node; distributing all to-be-processed tasks to different edge nodes for processing to serve as a habitat distribution scheme, and randomly generating an initial population with a plurality of habitat distribution schemes; and based on a preset target function and a biogeography optimization algorithm, acquiring an optimal solution meeting the target function, and acquiring a to-be-processed task which should be allocated to each edge node. The cloud collaborative multi-task scheduling method is based on the presettarget function and the biogeography optimization algorithm, acquires the optimal solution meeting the target function, obtains the to-be-processed task to be allocated to each edge node, considers reasonable task allocation of all the edge nodes and the central cloud node, can obtain the optimal allocation scheme meeting the optimization target based on the preset target function, is implementedbased on the biogeography optimization algorithm, and greatly reduces the calculation overhead.

Description

technical field [0001] The present invention relates to the field of edge computing, and in particular to a cloud collaborative multi-task scheduling method and device. Background technique [0002] Cloud-edge collaborative task scheduling is a process in which massive smart terminal devices offload computationally intensive tasks to the cloud server for optimization. It is very important in scenarios with high performance requirements such as system delay and energy consumption. Under the background of the Internet of Everything, there are many types of network edge devices, and there are many applications with high computing requirements, such as face recognition, interactive games, and augmented reality. These applications have a large amount of data, have high requirements for delay, and consume a large amount of computing resources and energy. Therefore, it is considered to offload the computing tasks of terminal devices to remote execution. [0003] Edge nodes are clo...

AI Technical Summary

Problems solved by technology

However, the current method is only limited to the collaboration between multiple edge nodes or the collaboration between the current edge node and the central cloud, and cannot realize the overall coordinated scheduling of the central cloud and all edge nodes, which will lead to a huge amount of calculation

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