IoV Data Transmission Bandwidth Prediction
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Solution Overview
Problem
Conventional data transmission methods in the Internet of Vehicles (IoV) are inefficient due to varying network bandwidth and differing data transmission requirements among various sensors, leading to inadequate utilization of network resources and timeliness issues, especially in unstable network environments.
Innovation Solution
A method that involves predicting network bandwidth and determining configuration information for data transmission based on the predicted bandwidth and specific data transmission configurations, allowing for optimized data transmission planning within defined time windows, thereby ensuring timely and efficient data delivery while adapting to changing network conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional data transmission methods are used in IoV, then data can be transmitted without complex prediction mechanisms, but network resource utilization is inadequate and transmission timeliness deteriorates due to varying bandwidth and unstable network conditions
Solution Approach 1:
The patent applies preliminary action by predicting network bandwidth in advance for future time windows and pre-determining data transmission configurations before actual transmission occurs. This allows the system to proactively plan data transmission schedules based on predicted network conditions, ensuring critical data is prioritized and transmitted timely even as network conditions change during vehicle movement.
2Productivity
If data transmission configurations are not optimized, then transmission processes are simple, but network resource utilization deteriorates due to lack of prioritization among different data types
Solution Approach 1:
The patent applies local quality by determining specific transmission configurations for different data types based on their individual characteristics and requirements. Each data type receives customized transmission parameters (such as priority levels, timing, and bandwidth allocation) tailored to its specific needs, rather than applying a uniform transmission approach to all data. This enables optimized network resource utilization while maintaining manageable configuration complexity through systematic differentiation.
3Productivity
If transmission planning is not adapted to network changes, then planning processes are simple, but transmission efficiency deteriorates in unstable network environments during vehicle movement
Solution Approach 1:
The patent applies dynamics by implementing a dynamic transmission planning approach where bandwidth is predicted for multiple future time windows and transmission configurations are determined adaptively for each window. As network conditions change during vehicle movement, the system continuously updates predictions and re-determines optimal transmission schedules, enabling efficient adaptation to unstable network environments while maintaining structured transmission control.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for data transmission. In one embodiment, a method includes: receiving a plurality of types of data at a first device from a plurality of data sources, each type of data having a corresponding data transmission configuration; determining a first predicted network bandwidth for transmitting data from the first device to a second device in a first time window period in the future; determining a first piece of configuration information for transmitting the plurality of types of data in the first time window period based on the first predicted network bandwidth and a plurality of data transmission configurations corresponding to the plurality of types of data; and transmitting the received plurality of types of data to the second device in the first time window period based on the first piece of configuration information.