A vehicle task data scheduling method based on edge computing

Abstract

The invention discloses a method for dispatching vehicle task data based on edge computing. The method includes: when an edge computing station determines that a vehicle enters the coverage area, acquires the terminal task attribute and the vehicle driving route of the incoming vehicle, and determines the passing of the vehicle. The environmental information when covering the area, according to the environmental information and terminal task attributes, determine the various task data generated by the vehicle passing through the coverage area; determine the computing resources required for processing various task data, compare and determine the maximum computing resources, and judge the forecast of the current edge computing station. Whether the reserved computing resource is greater than the maximum computing resource; if it is larger, take the current edge computing station as the first target edge computing station and establish a communication connection; if it is smaller, match the reserved computing resources and presets according to the surrounding adjacent edge computing stations The method determines a second target edge computing station and establishes a communication connection. The vehicle task data scheduling method of edge computing in the present invention ensures the timeliness and high efficiency of vehicle task processing.

Description

technical field [0001] The invention relates to the technical field of edge computing, in particular to a method for scheduling vehicle task data based on edge computing. Background technique [0002] Edge computing refers to the use of an open platform that integrates network, computing, storage, and application core capabilities on the side close to the source of objects or data to provide the most recent services nearby. Edge computing is compatible with traditional cloud computing. Edge computing can use limited local resources to perform preliminary processing of data and then send it to the remote cloud for further processing. On the other hand, edge computing can also handle some latency-sensitive or geographically related applications alone, which can guarantee lower latency and energy consumption. [0003] The development and application of the Internet of Vehicles has further promoted the emergence of edge computing models. The typical edge computing model for the...

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Problems solved by technology

[0003] The development and application of the Internet of Vehicles has further promoted the emergence of the edge computing model. The typical edge computing model for the Internet of Vehicles is to distribute corresponding edge computing stations in each area to process the task data of the vehicles in the area. However, due to the Depending on the vehicle type, terminal type, and vehicle driving environment, the amount of task data and task type generated by the vehicle end are also different. When the number of vehicles in a certain area is large or the amount of task data generated at the same time is large, the corresponding area will appear. The edge computing station in the network cannot meet the task data processing requirements of the vehicles in its coverage area, resulting in the inability to complete the monitoring function of the vehicle

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