Multitask-oriented edge computing resource allocation method

Abstract

The invention discloses a multitask-oriented edge computing resource allocation method, which comprises the following steps of: 1) constructing an edge computing network scene to obtain a data parameter of a mobile terminal task and a performance parameter of an edge server; 2) allocating channel resources according to the data parameters of the task, calculating the transmission delay of the task, and calculating the residual maximum delay limit of the task; 3) comparing whether the maximum number of tasks simultaneously executed by the edge server is smaller than the number of unloaded tasks, if not, executing the step S4, and if yes, executing the step S5; 4) allocating computing resources to different unloading tasks according to the size relationship between the computing resources ofthe edge server and the minimum computing resources required for completing the tasks and different optimization objectives; and 5) reasonably scheduling the tasks, determining the execution startingtime of each task, and allocating the computing resources to each task. Dynamic allocation of the computing resources on the edge server is realized, and the total time delay of task unloading is reduced.

Description

technical field [0001] The present invention relates to mobile communication technology, in particular to a multi-task-oriented edge computing resource allocation method. Background technique [0002] With the advent of the Internet of Everything era, various smart mobile devices have been widely used in people's lives, resulting in the explosive growth of mobile devices and generating massive amounts of mobile data. However, the limited battery capacity and computing and storage resources of mobile devices cannot handle huge amounts of data in a short period of time. One solution is to offload part of the work to a resource-rich remote cloud server for processing, that is, cloud computing. However, uploading a large amount of mobile data to the cloud center will lead to an excessive amount of data in the transmission link, resulting in network congestion. In addition, the long transmission distance between the mobile terminal and the cloud computing center will cause signi...

AI Technical Summary

Problems solved by technology

However, on the one hand, a large amount of food data will lead to high network load and channel congestion. On the other hand, the long transmission distance brings high delay, and the data processing results cannot be given in time, so that food safety related events cannot be timely Supervision

At the same time, when meat is contaminated or not operated according to regulations, a long response delay will lead to late result feedback and response measures, which may cause irreversible damage to food safety

Images