Online computing task unloading scheduling method for edge computing environment

Abstract

The invention discloses an online computing task unloading scheduling method for an edge computing environment, which is based on a dynamic Cournot game model and comprises the following steps that: aserver periodically publishes the rental price of computing resources; each application of each user equipment generates a calculation task according to a certain frequency; when a calculation task is generated, the user equipment calculates the number of rented calculation resources by using the obtained price information and historical information and a designed iterative algorithm, determinespayment function values obtained by calculation on different servers, selects an optimal scheduling mode in real time, and sends a calculation task request; the server receives a user equipment request, allocates computing resources in real time, and updates the rental price; and after calculation is completed, the user equipment receives result data and updates historical information, so that dynamic circulation is carried out, Nash equilibrium is achieved, and global optimization is realized. The method is low in calculation amount, small in communication overhead, high in real-time performance and suitable for differentiated user experience quality requirements of a dynamic network environment and different applications.

Description

Technical field [0001] The invention belongs to the technical field of edge computing optimization, and particularly relates to an online computing task offloading scheduling method. Background technique [0002] With the development of mobile smart devices and the increasing demand of users for application service quality, in addition to the difficulties in the development of algorithms, new fundamental problems have also been exposed: the more abundant computer applications are used in mobile devices, Mobile devices require more computing resources and have sensitive delay constraints, which means that higher demands are placed on the computing power of mobile devices. [0003] In recent years, the research and development of communication technology and edge computing technology has provided a new idea to solve this problem: use edge computing to share the pressure of computing tasks on the mobile terminal. For example, in the field of autonomous driving, SLAM (Simultaneous Loc...

AI Technical Summary

Problems solved by technology

In response to this problem, the current online method adopts the method of dividing time slices. For example, in the paper "A mobilityaware vehicular caching scheme in content centric networks: Model and optimization", the Markov chain is used to model discrete time slices and thus the centralized optimization method is adopted. Mainly there is the problem of poor real-time performance; there are also methods based on real-time network status monitoring, such as a method for unloading automatic driving service

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