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

A task queue and edge computing technology, applied in the field of distributed computing, can solve problems such as large computing delay, large computing delay, and increased average delay of application tasks, achieving good stability, low average delay, and reduced computing The effect of delay

Pending Publication Date: 2022-04-19
SHANGHAI UNIV
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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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  • Task queue aware edge computing real-time channel allocation and task unloading method
  • Task queue aware edge computing real-time channel allocation and task unloading method
  • Task queue aware edge computing real-time channel allocation and task unloading method

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Embodiment Construction

[0042] The experimental environment of this embodiment is Windows10 64bit operating system, the CPU is Intel i7-7600U, the memory is 16GB, and the development language of the experiment is Python. The MEC network scenario includes an edge server and a base station. There are L subchannels in the base station, that is, l∈L={1,2,...,L}; there are M service requesting users in its coverage area, that is, m∈M= {1,2,...,M}; each user has K types of application requests, that is, k∈K={1,2,...,K}; the average task generation size of k types of applications is B k , the same application task size b m,k,j Obeying the mean is B k The uniform distribution of k-type application tasks requires a calculation amount per bit of μ k .

[0043] The time domain is divided into T time slots, that is, t∈T={1,2,...,T}, the duration of each time slot is ΔT, and the k-type applications of user m are in T time slots. share in gap tasks whose indexes are sorted by arrival time are

[0044] ...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W72/08H04L43/0852H04W28/16H04W72/04
CPCH04W28/16H04L43/0852H04W72/53H04W72/542
Inventor 孙彦赞谢新坤张舜卿吴雅婷王涛
Owner SHANGHAI UNIV
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