Particle swarm-based service migration method in edge computing environment

Abstract

The invention relates to a service migration method based on a particle swarm in an edge computing environment, and belongs to the technical field of mobile communication. The method comprises the following steps: S1, modeling a server; S2, reporting a service request: equipment sends own state information to a local network controller; S3, finding out the equipment of which the delay does not meet the requirement: the local network controller estimates the delay of the equipment according to the received equipment state information and the network information collected by the state collectionmodule, and judges whether the delay requirement of the corresponding type of task is met or not; and S4, formulating a migration decision: selecting the equipment which cannot meet the requirementsfor the server, comprehensively considering energy consumption and time delay in combination with factors such as task size, task type, link stability, server state and the like, and formulating the migration decision with the maximum income. According to the invention, service migration can be triggered in real time when the equipment performance does not reach the standard, and the income of service migration is maximized while the task requirements of each piece of equipment are met.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to a particle swarm-based service migration method in an edge computing environment. Background technique [0002] Mobile cloud computing technology, which is an integration of cloud computing and mobile computing, has been widely used in the past few years, which relies heavily on the centralization of computing and data resources so that these resources can be distributed by end-users in an orderly manner. In other words, the data processing, calculation and even storage of the application do not need to be performed on the mobile device with limited processing power, which greatly reduces the application's requirements on the hardware of the mobile device. However, because the cloud service is provided by a large centralized data center far away from the user, the user needs to bear the long delay caused by the connection with the remote cloud data center, and the data...

AI Technical Summary

Problems solved by technology

[0005] Most of the existing service migration strategies are not comprehensive enough, or they mainly make decisions from the network side, based on information such as load and user requests, without considering the impact of user mobility, or only optimize a single performance index, without comprehensively considering multiple performances In the case of indicators, either a one-dimensional mobility model is used to analyze device mobility, which cannot truly reflect the mobility of devices in actual scenarios, or only a service migration is performed in a fixed period of time, rather than triggering service migration at any time, and service migration efficiency too low

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