Edge computing task cooperative scheduling method, system and device

Abstract

The invention belongs to the technical field of edge computing, particularly relates to an edge computing task cooperative scheduling method, system and device, and aims to solve the problems that anant colony algorithm is prone to local optimization and cannot well solve the problems of low resource utilization rate and unbalanced virtual machine computing resource load in an edge environment. The method comprises the steps of obtaining a scheduling queue of an edge computing task, and initializing related parameters; starting from the first ant in the ant colony algorithm, obtaining a feasible solution of the current ant; if the solution is the optimal feasible solution, updating the optimal solution and the shortest task maximum completion time; updating local pheromones until all antscomplete solution searching; carrying out global pheromone updating, and carrying out local optimization in an iterative mode until the set number of iterations is reached, and obtaining a globally optimal feasible solution and the corresponding shortest task maximum completion time are obtained. According to the method, the ant colony algorithm is further prevented from falling into local optimum too early, and load balance, reasonable task scheduling and efficient resource utilization are guaranteed.

Description

technical field [0001] The invention belongs to the technical field of edge computing, and in particular relates to a method, system, and device for collaborative scheduling of edge computing tasks. Background technique [0002] Edge computing is a computing model that uses computing, network, storage and other resources to form a unified resource platform on the edge of the network close to the data source to provide services for users. Together with cloud computing, it becomes a complementary computing solution to the application needs of the Internet of Things. paradigm. At present, the edge computing environment is composed of multiple edge computing nodes and edge servers. How to efficiently utilize resources such as computing, storage, and bandwidth of these nodes is particularly important. The task scheduling strategy under edge computing is an effective way to rationally utilize resources in the edge environment. An efficient task scheduling strategy is very importa...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the above problems in the prior art, that is, the ant colony algorithm is prone to local optima and cannot well solve the problems of low resource utilization and unbalanced load of virtual machine computing resources in the edge environment, the present invention provides a A method for collaborative scheduling of edge computing tasks, the method comprising:

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