A Data Scheduling Method Based on Vehicle Collaboration in Urban Scenarios
A data scheduling and scene technology, applied in the field of vehicle network, can solve the problem that it is difficult for a single vehicle to meet data requests
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2018-10-30
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Abstract
Description
technical field
[0001] The invention relates to a data scheduling method based on a vehicle network in an urban scene, more particularly, a data scheduling method using a cooperative download mechanism in an urban scene, and belongs to the technical field of a vehicle network. Background technique
[0002] Vehicle Ad-hoc Network (VANET) is a vehicle with an onboard unit (OBU) running on the road, and a roadside unit (RSU, sometimes called a roadside foundation) deployed on the roadside. Facilities Infrastructure), control or service centers on the Internet, and electronic devices carried by individuals. It includes three basic communication modes: communication between vehicles (V2V, Vehicle-to-Vehicle), communication between vehicles and roadside units (V2I, Vehicle-to-Infrastructure or I2V, Infrastructure-to -Vehicle) and communication between vehicles and people (V2P, Vehicle-to-People). The in-vehicle network transforms all driving vehicles into mobile wireless nodes o...
Examples
Embodiment 1
[0212] Through the simulation experiment on the vehicle network simulation software NS2 (Network Simulator), the configured simulation experiment configuration parameters:
[0213]
[0214] Experimental results such as Figure 5 shown. The roadside unit executes the speed prediction proposed by the present invention, and according to the prediction result, the scheduling transmission of the request data is carried out to the requesting vehicle and the cooperative vehicle, and the data downloading amount is obviously higher than that of the data transmission scheduling method not using the prediction mechanism (improved 35% to 50%), improving the data download rate.