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Traffic data-oriented end-edge cooperative computing unloading method

A technology for computing unloading and traffic data, applied in computing, electrical digital data processing, program control design, etc., can solve problems that are not suitable for the field of intelligent transportation, and achieve the effect of excellent performance and resource allocation

Active Publication Date: 2020-03-27
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0006] In order to solve the problem that the computing offloading algorithm in the prior art is not suitable for the field of intelligent transportation, the present invention provides a traffic data-oriented end-side collaborative computing offloading method

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  • Traffic data-oriented end-edge cooperative computing unloading method
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  • Traffic data-oriented end-edge cooperative computing unloading method

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specific Embodiment I

[0068] Specific embodiment I: the vehicle driving map captured by the camera device, when the front-end camera needs to process a task with a small amount of calculation such as how many vehicles there are, then there is no need to offload the calculation task to the edge computing node for execution, only need to be in Running in the camera device, the running time is the local processing time: c i Indicates the number of computing resources required for the i-th task, f i Represents the computing resources of a camera device.

[0069] When processing tasks with a large amount of calculation, such as recognizing license plates and vehicle colors, it is necessary to offload the calculation tasks to edge computing nodes for execution. Here, only the total delay of calculation offloading in the case of wired communication is described. Assuming that the i-th camera device at the intersection requests computing tasks from the j-th edge computing node, the communication time is...

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Abstract

In order to solve the problem that a calculation computing algorithm in the prior art is not suitable for the field of intelligent transportation, the invention provides a traffic data-oriented end-edge cooperative computing unloading method, which comprises the following steps: firstly, establishing a system model for communication time delay and calculation time delay; then establishing a systemutility function taking time delay and resources as constraint conditions; and finally, designing an optimization strategy to obtain balance between the two. In the computing unloading process, calculation resources and time delay are comprehensively considered, and an optimization function is designed to obtain balance between the calculation resources and the time delay. The traffic data-oriented end-edge cooperative computing unloading method firstly establishes a total time delay system model according to a communication time system model, an edge side calculation time system model and alocal calculation time system model, then comprehensively considers the balance of resource allocation, designs a system utility function, finally, researches a system optimization strategy, and completes the design of a calculation unloading algorithm. According to the characteristics of intelligent transportation industry application, resource allocation and time delay are considered in the design process, and the performance is superior to that of a traditional algorithm.

Description

technical field [0001] The invention relates to the technical field of task offloading of the Internet of Things, in particular to a traffic data-oriented end-edge collaborative computing offloading method. Background technique [0002] With the continuous development of intelligent transportation technology, the data generated by traffic sensing equipment and control systems is constantly increasing, which makes the demand for data computing and processing capabilities continue to increase. To deal with this kind of demand, the first thing to consider is of course cloud computing technology. Its advantage is mainly that centralized cloud servers provide super computing power and computing resources. However, in intelligent transportation systems, when dealing with these computing-intensive and delay-sensitive tasks, due to the relatively high requirements for delay, edge computing happens to have the feature of being closer to the computing power of front-end devices to eli...

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Application Information

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IPC IPC(8): G06F9/50
CPCG06F9/5072G06F9/5088G06F2209/502G06F2209/508G06F2209/509
Inventor 何琦刘建圻尹秀文辛苗何威赵静
Owner GUANGDONG UNIV OF TECH
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