Internet of Things service low-delay load distribution method and device based on edge computing

Abstract

The embodiment of the invention provides an Internet of Things service low-delay load distribution method and device based on edge computing. The Internet of Things service low-delay load distributionmethod comprises the steps: acquiring a task request of each application in each terminal and the computing capacity of each edge node; and inputting the task request of each application in each terminal and the computing capacity of each edge node into a preset optimization problem model, and outputting a resource allocation matrix and a task allocation matrix, wherein the preset optimization problem model comprises a particle swarm algorithm model improved through an ant colony algorithm and a semi-definite relaxation algorithm model improved through a Gaussian random algorithm. The Internet of Things service low-delay load distribution method and device based on edge computing improve particle swarm optimization by applying the ant colony algorithm, reduce the convergence time of the algorithm, improve the performance of the resource allocation result, solve the rank 1 constraint in the semi-definite relaxation problem by applying the Gaussian random variable, improve the performance of the task allocation result, and finally reduce the service delay.

Description

technical field [0001] The present invention relates to the technical field of the Internet of Things, in particular to a method and device for low-latency load distribution of Internet of Things services based on edge computing. Background technique [0002] The power Internet of Things is the product of the application of Internet of Things technology to the smart grid. With the intelligentization of terminals and the diversification of functions, more and more services have put forward extremely high requirements for service delay. However, in the traditional cloud computing architecture, uploading data to remote cloud servers consumes a lot of transmission time, and the limited bandwidth of the core network cannot withstand massive data transmission. As a new computing technology closer to the business terminal, edge computing has become an effective solution for the power Internet of Things to handle delay-sensitive business. [0003] Edge nodes are located at the edge...

AI Technical Summary

Problems solved by technology

[0008] However, technical solution 1 is difficult to guarantee the stability of the sub-cluster of IoT devices, and the cost of maintaining and updating the sub-cluster of IoT devices is relatively high, and it is difficult to meet the requirements when processing delay-sensitive services

Technical solution 2 only solves the load balancing between peer nodes in the network, and does not distinguish the difference of task types on t

Images