Multi-access edge computing task unloading method based on boxing problem

Abstract

The invention provides a multi-access edge computing task unloading method based on a boxing problem. According to the method, a user terminal and edge servers are regarded as task containers, and tasks are regarded as articles, so that a task unloading decision problem in edge calculation is converted into a boxing problem, the number of the edge servers started in a network is minimized througha heuristic method, and a task unloading decision is solved. The method comprises the following steps that firstly, calculating the loading capacity of each edge server and the ratio of the input datasize of each terminal task to resources needing to be calculated; forming two queues according to the capacity loading capacity and the task ratio from large to small; and finally, sequentially taking out the tasks in the task queue, configuring the tasks to an edge server with the maximum capacity and residual computing resources in the container queue, and repeating the operation until the taskqueue is empty. The method can be suitable for the task processing process of a multi-terminal and multi-task multi-access edge computing network, an appropriate task unloading scheme can be clearlyformulated, the computing energy consumption is minimized while the task time delay requirement is met, and the cost is saved.

Description

technical field [0001] The invention relates to the field of multi-access edge computing, in particular to the problem of computing resource allocation of multiple edge servers in a multi-access edge computing network. Background technique [0002] The Internet of Things (IoT) technology aims to use radio frequency identification technology, wireless data communication technology, global positioning system, etc., to connect physical objects with the Internet according to the communication protocol agreed by the Internet of Things, and then realize information exchange and achieve intelligence. The purpose of identifying, locating, tracking, monitoring and managing Internet resources. With the increase in the number of devices, the enhancement of computing performance, and the continuous growth of user needs, edge computing has become an important expansion form of the Internet of Things. Multi-access Edge Computing (Multi-access Edge Computing, MEC) is an emerging concept i...

AI Technical Summary

Problems solved by technology

In the traditional terminal execution mode, if computing-intensive tasks are completely executed locally on the terminal, it may lead to excessive energy consumption of the terminal, long task running time, and failure to meet the operating requirements of complex applications.

On the contrary, if all the data of the terminal is sent to the cloud center for processing, although it can meet the precise calculation requirements of complex applications, it will greatly increase the load on the cloud center and network links, and also cause excessive communication energy consumption of the terminal

And because the distance between the terminal and the cloud is too long, it will cause a high transmission delay, which cannot meet the low-latency requirements of some terminal applications.

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