Task queue aware edge computing real-time channel allocation and task unloading method

Abstract

An edge computing real-time channel allocation and task unloading method based on task queue perception is characterized in that a base station channel allocation and user task unloading problem based on task queue perception is converted into a single time slot optimization model according to a Lyapunov optimization framework, users are divided and combined according to a game theory, and a cooperative game is carried out; and forming a combination set with stable convergence, and finally obtaining a channel allocation and task unloading strategy of each time slot.

Description

technical field [0001] The invention relates to a technology in the field of distributed computing, in particular to a real-time channel allocation and task unloading method based on Lyapunov optimization and game theory task queue backlog perception. Background technique [0002] Mobile Edge Computing (MEC) is widely regarded as an important technology to realize the vision of the next generation Internet. Traditional cloud computing systems rely on remote public clouds, which will cause long delays due to data exchange. MEC deploys a cloud computing platform at the edge of the wireless access network to provide computing, storage, network and communication resources for application services. Can ease the tension between compute-intensive applications and resource-constrained mobile devices. Therefore, by offloading computing tasks on mobile devices to MEC servers, the distance to application services can be shortened, thereby reducing energy consumption and execution dela...

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Problems solved by technology

[0004] The present invention aims at the large wireless transmission delay and task calculation delay caused by channel allocation in the prior art, and the inability to perceive the status of different types of task queues of the MEC server, so that too many tasks of the same type arrive at the same time, resulting in a backlog of tasks in the task queue Excessive computing delays are caused by too many problems, and in densely populated places, the backlog of task queues of individual application services in edge servers leads to an increase in the average delay of all application tasks. A task queue-aware edge computing real-time channel is proposed. The allocation and task offloading method, based on the Lyapunov optimization framework, performs single-slot goal conversion, analyzes the backlog of task queues in the edge server and the remaining time of tasks, and uses game algorithms to perform real-time channel allocation and task offloading on user equipment. In order to minimize the average delay of tasks

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