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Task unloading and dispatching method in multi-access edge computing system

A technology for edge computing and computing tasks, applied in electrical components, wireless communication, etc., can solve the problem of not considering the task assignment of the edge end

Active Publication Date: 2021-03-16
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Considering the selfishness of each mobile device (that is, each device wants to minimize its own task completion delay) and the selfishness of wireless access points (minimizing the total completion delay of received tasks), The task offloading and assignment problem is a complex one due to the interactivity of offloading decisions for mobile devices and assignment decisions for APs and the absence of a centralized operator to make joint decisions for all mobile devices and APs
In recent years, although some related works have studied the problem of task offloading in edge computing systems, they did not consider the task assignment between edge terminals, thus failing to make full use of wireless access points with multiple wired connections. The computing resources of the multi-access edge computing system

Method used

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  • Task unloading and dispatching method in multi-access edge computing system
  • Task unloading and dispatching method in multi-access edge computing system
  • Task unloading and dispatching method in multi-access edge computing system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] see figure 1 , a task offloading and dispatching method in a multi-access edge computing system, the operation steps are as follows:

[0054] Step 1, modeling the edge computing system;

[0055] Step 2, modeling the communication and execution modes of computing tasks;

[0056] Step 3, formalize the problem of task offloading and assignment, and model it as a multi-master-slave Stackelberg game;

[0057] Step 4, prove the existence of Stackelberg equilibrium of the task unloading and assignment problem, and propose its effective algorithm.

[0058] The method of this embodiment designs a decentralized decision-making algorithm for mobile smart devices and wireless access points, so as to minimize the completion delay of each computing task in the edge computing system.

Embodiment 2

[0060] This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0061] In this example, see Figure 1-3 , in the step one, model the edge computing system; the multi-access edge computing system includes M wireless access points acting as edge nodes and N mobile smart devices Each access point is equipped with an edge server with greater computing power than the mobile device; and for each access point and each mobile device Computational power, that is, CPU frequency; each mobile device i has a computing task to perform where s i Enter the data size for this task, c iis the number of CPU cycles required for the task; all access points are connected to each other through optical fibers in the core network; each mobile device i∈N accesses one or more access points through wireless channels, and each mobile device can only communicate with An access point communicates; the set of access points accessible to mobile device i ...

Embodiment 3

[0084] see image 3 , a distributed task offloading and dispatching method in a multi-access edge computing system, the operation steps are:

[0085] Step 1, modeling the edge computing system. The multi-access edge computing system in this embodiment includes M wireless access points acting as edge nodes and N mobile smart devices Each access point is equipped with an edge server with more computing power than the mobile device. use and Indicates the computing power of each access point m ∈ M and each mobile device i ∈ N, that is, the CPU frequency. Each mobile device i has a computational task to perform where s i Enter the data size for this task, c i The number of CPU cycles required for the task. All access points are connected to each other via optical fibers in the core network. Each mobile device i∈N can access one or more access points through wireless channels (note that each mobile device can only communicate with one access point at a time). The set ...

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Abstract

The invention relates to a task unloading and dispatching method in a multi-access edge computing system, in particular to an unloading and dispatching method for minimizing the completion time delayof each task in an edge computing system. In the edge computing system considering selfish of a mobile device and a wireless access point, a task unloading and dispatching problem is modeled into a multi-master-slave Stackelberg game, and a decentralization method is designed to enable mobile equipment to autonomously select an unloading decision and balance the workload of a wireless access point, so that the time delay solved by each task is minimized. An algorithm is not adopted to execute the following steps in sequence: firstly, an unloading strategy updating method based on a Q value isadopted to calculate an optimal task unloading decision for each mobile intelligent device; then, the task assignment decision balance of each access point is updated based on an optimal response dynamic method; and the above steps are repeated until the unloading decision of the mobile device converges.

Description

technical field [0001] The present invention relates to a task offloading and dispatching method in a multi-access edge computing system, which is a method of offloading and dispatching that minimizes task completion delay in an edge computing system, in a wireless access point with multiple edge nodes And in an edge computing system with multiple mobile devices that can be wirelessly connected to edge nodes, considering the selfishness of mobile devices and wireless access points, by deciding whether the computing tasks generated by mobile devices are executed locally or are distributed to To a certain wireless access point, the completion delay of each computing task is minimized. Background technique [0002] Today, with the rapid growth of mobile devices, many computing-intensive applications, such as online interactive games and augmented reality, have emerged. In the resulting cloud computing model, computing tasks are offloaded to remote cloud servers for processing,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W24/02H04W24/06
CPCH04W24/02H04W24/06Y02D30/70
Inventor 刘通方璐童维勤李卫民
Owner SHANGHAI UNIV
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