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Cloud edge collaborative task allocation management method and system based on edge computing

An edge computing and task allocation technology, applied in the field of Internet of Vehicles, can solve the problems of chaotic and diverse edge computing task allocation management methods, large fluctuations in completion efficiency, and limited efficiency.

Pending Publication Date: 2022-04-29
GUANGDONG POWER GRID CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0002] In the prior art, most of the Internet of Vehicles systems rely on wireless networks, that is, mainly rely on the cloud center to operate, and the efficiency of task allocation management is limited by the vehicle equipment and network environment. With the application of edge computing technology, task allocation is gradually Shifting to the edge side, however, the existing edge computing task allocation and management methods are messy and diverse, and the completion efficiency level fluctuates greatly

Method used

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  • Cloud edge collaborative task allocation management method and system based on edge computing
  • Cloud edge collaborative task allocation management method and system based on edge computing
  • Cloud edge collaborative task allocation management method and system based on edge computing

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Embodiment 1

[0037] refer to figure 1 , which is an embodiment of the present invention, provides an edge computing-based cloud-edge collaborative task allocation management method, including:

[0038] S1: Use the collection module 100 to collect the operating data of the equipment in real time.

[0039] It should be noted that the operating data of the equipment includes the operating data obtained by real-time reading according to the set measuring points.

[0040] S2: Preprocessing the operating data. Based on the preprocessed operating data, the edge computing module 200 performs data analysis and processing according to the computing tasks assigned by the collaborative strategy module 400 .

[0041] It should be noted that the preprocessing operation data includes:

[0042] Clean up blank values, format content, logic errors, and non-required operating data;

[0043] Carry out feature construction, data classification and data quantification on operating data;

[0044] Perform data ...

Embodiment 2

[0083] refer to figure 2 It is another embodiment of the present invention. This embodiment is different from the first embodiment in that it provides an edge computing-based cloud-edge collaborative task allocation management system. The above-mentioned edge computing-based cloud-edge collaborative task allocation management method can Relying on the realization of this system.

[0084] Specifically, the system includes:

[0085] The collection module 100 is used for real-time collection of operating data of the equipment;

[0086] The edge computing module 200 is connected to the acquisition module 100 through the collaborative strategy module 400, and is used to perform data analysis and processing according to the computing tasks assigned by the collaborative strategy module 400;

[0087] Wherein, in the process of data analysis and processing, the database cyclic learning module 500 is used to continuously cyclically learn the equipment fault codes and judge the size a...

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Abstract

The invention discloses a cloud edge collaborative task allocation management method and system based on edge computing. The method comprises the following steps: acquiring operation data of equipment in real time by using an acquisition module; preprocessing the operation data, and based on the preprocessed operation data, performing data analysis and processing by the edge calculation module according to the calculation task allocated by the collaborative strategy module; and matching a corresponding control instruction according to the analysis and processing result, and controlling the operation of the equipment by an execution module according to the obtained control instruction. According to the method, the limitation probability which has important influence on the research search target can be generated for the comprehensiveness of the perception data, the task completion efficiency, the quality of the perception data and the like, and the effect of an edge cloud collaboration mode of task allocation is realized according to the formulated edge task allocation strategy.

Description

technical field [0001] The present invention relates to the technical field of the Internet of Vehicles, in particular to a cloud-edge collaborative task allocation management method and system based on edge computing. Background technique [0002] In the prior art, most of the Internet of Vehicles systems rely on wireless networks, that is, mainly rely on the cloud center to operate, and the efficiency of task allocation management is limited by the vehicle equipment and network environment. With the application of edge computing technology, task allocation is gradually Shifting to the edge side, however, the existing edge computing task allocation and management methods are messy and diverse, and the level of completion efficiency fluctuates greatly. Contents of the invention [0003] The purpose of this section is to outline some aspects of embodiments of the invention and briefly describe some preferred embodiments. Some simplifications or omissions may be made in thi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06F16/2458G06F16/2455G06K9/62G06N3/04
CPCG06F9/5027G06F9/5072G06F16/2462G06F16/24564G06N3/04G06F2209/502G06F18/241
Inventor 曾纪钧龙震岳张小陆梁哲恒
Owner GUANGDONG POWER GRID CO LTD
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