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A task collaborative planning method and system for smart factories

A task and factory technology, applied in the field of data processing, can solve the problems of large information security threats, increased transmission costs, lack of parallel execution methods for artificial intelligence tasks, etc., to reduce production costs, reduce delays and energy consumption, and realize The effect of sensitive needs

Active Publication Date: 2022-04-22
JIANGXI XINBORUI TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, compared with edge-edge links, edge-cloud links are more vulnerable to attacks and are subject to greater information security threats, resulting in higher maintenance costs for edge-cloud links
[0006] 2) At present, most of the intelligent production algorithms at home and abroad lack the parallel execution mode of artificial intelligence tasks. Therefore, there is a problem of insufficient optimization for artificial intelligence production
[0007] 3) At present, most edge intelligent algorithm designs at this stage only focus on one-to-one task allocation, ignoring the task coordination problem between edge nodes
[0008] 4) Most of the existing edge intelligence algorithms ignore the location deployment design of edge nodes, and there is a problem of increased transmission costs due to unreasonable location design

Method used

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  • A task collaborative planning method and system for smart factories
  • A task collaborative planning method and system for smart factories
  • A task collaborative planning method and system for smart factories

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] Such as figure 1 As shown, the present application provides a method for collaborative task planning for smart factories, which includes the following steps:

[0061] Step S1, collecting interaction information data between IoT devices and edge node devices in the edge collaborative intelligent architecture.

[0062] Establish an ad hoc network in the edge node network in advance, build an edge collaborative intelligent architecture based on the ad hoc network, set the ad hoc network composed of M edge node devices that can be used for task computing in the edge node network, and set the task collaboration strategy update The period is T S , at period T S There are K Internet of Things (IoTs) devices in China.

[0063] A virtual cloud based on an ad hoc network does not need to rely on a remote server, but a group of mobile devices cooperate to calculate and complete tasks.

[0064] Define the total system cost in the edge collaborative intelligent architecture as f...

Embodiment 2

[0117] Such as Figure 5 and 6 As shown, the present application provides a smart factory-oriented task collaborative planning system 100, the system includes: an edge collaborative intelligent architecture 10 based on an ad hoc network, and the edge collaborative intelligent architecture 10 includes a plurality of IoT devices 11 and a plurality of edge nodes A device 12; a plurality of IoT devices 11 and a plurality of edge node devices 12 are communicatively connected; a plurality of edge node devices 12 perform task coordination.

[0118] A data collection device 20, configured to collect interaction information data between the IoT device and the edge node device in the edge collaborative intelligent architecture;

[0119] The data processor 30 is configured to calculate the location deployment cost of the edge node device according to the interaction information data;

[0120] The obtaining module 40 is used to obtain the location data of each edge node device and compu...

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Abstract

The present application provides a task collaborative planning method and system for smart factories. The method includes the following steps: collecting interactive information data between IoT devices and edge node devices in the edge collaborative intelligent architecture; calculating the cost of edge node location deployment; obtaining edge nodes The location data of each edge node when the location deployment cost is the optimal solution; calculate the selection cost of each edge node based on the location data of the edge node and computing resource information data, and obtain the edge node with the lowest selection cost as the core node device; At the node device, collect the task information data of the current task cycle; calculate the task execution cost according to the task information data; obtain the task collaboration strategy when the task execution cost is optimal. The application reduces the selection cost of core node equipment and edge node location deployment costs in artificial intelligence production tasks, and makes task execution cost less loss and task processing delay smaller.

Description

technical field [0001] The present application relates to the technical field of data processing, and in particular to a method and system for collaborative task planning for smart factories. Background technique [0002] In recent years, major economies around the world have vigorously promoted the revival of the manufacturing industry. Among them, intelligent production is the main line of intelligent manufacturing, and intelligent factory is the main carrier of intelligent production. Under the upsurge of Industry 4.0, Industrial Internet, Internet of Things, and cloud computing, many excellent manufacturing companies around the world have carried out smart factory construction practices. In order to accelerate the implementation of smart factories, a variety of algorithms have emerged. Among them, the application of artificial intelligence algorithms to smart production has become a popular technology. [0003] However, due to the weak computing power and low battery c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L41/0826H04L41/0894H04L67/10H04L67/12G16Y10/25
CPCH04L41/0826H04L41/0893H04L67/10H04L67/12G16Y10/25
Inventor 陈泽仁张天魁陈潮彬徐琪章园王宇敬
Owner JIANGXI XINBORUI TECH CO LTD
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