Optimized task scheduling method in mobile edge computing

Abstract

An optimization task scheduling method in mobile edge computing comprises the steps: estimating the number of task migration failures according to historical data, modeling a task scheduling problem into an optimization problem about minimization of computing resource allocation variables and task scheduling variables, and converting the optimization problem into a set function optimization problem only about the task scheduling variables; obtaining a primary scheduling strategy suitable for all conditions according to the constructed linear approximation function of the target function, and further obtaining a secondary scheduling strategy according to the constructed sub-module approximation function of the target function when the computing power of the user is weaker than the computingpower of the server; and finally, obtaining an optimized task scheduling strategy through the primary scheduling strategy and the secondary scheduling strategy. According to the method, the delay ofthe computing task can be kept at a relatively low level when possible hardware and software faults occur.

Description

technical field [0001] The present invention relates to a technology in the field of mobile edge computing, in particular to a method for optimizing task scheduling in mobile edge computing. Background technique [0002] Due to the rapid development of various mobile applications and the Internet of Things (IoT), cloud infrastructure and wireless networks face stringent requirements such as ultra-low latency, high reliability, and continuity of user experience. These demands make end users at the edge of the network urgently need highly localized services, and a basic and key issue in mobile edge computing is the scheduling of user requests, that is, to determine which task should be migrated to which edge node for remote execution, so as to Meet various performance requirements. [0003] Compared with mobile cloud computing, mobile edge computing faces the following unique uncertainties in task migration. First, unlike mobile cloud computing, which mostly completes task m...

AI Technical Summary

Problems solved by technology

First, unlike mobile cloud computing, which mostly completes task migration through reliable wired links, since edge servers are usually deployed on local wireless access points or cellular base stations, mobile edge computing tasks are usually migrated to the edge through unreliable wireless links. node

In addition, uncertainties such as wireless network connection failures, low reliability of edge servers, etc. can make any pre-optimized task migration strategy fail, resulting in large performance losses, such as large response times

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