Highly Concurrent Data Processing Design for 5G C-V2X Intelligent Transportation Systems (ITS)
Bo Liu, W. Chris Chen, Zhengguo Sheng, Ahmed Barakat, Yong Liang Guan · 2024
Vehicle-to-Everything (V2X) technology plays a key role in enhancing road traffic safety, increasing transportation efficiency and reducing environmental pollution. The ongoing evolution of this technology suggests that future vehicular communication system will need to adapt to greater connectivity demands and more complex interactive scenarios. Particularly, the introduction of the 3rd Generation Partnership Project (3GPP) Rel. 16 SideLink standard has laid the groundwork for a plethora of enhanced vehicular applications (eV2X). However, there are new challenges brought by the limitations of traditional multi-threading approaches in processing large volumes of data. This study introduces a lightweight and highly concurrent data processing framework that offers a novel approach to enhance the data processing capability and scalability of V2X. Unlike traditional concurrent execution, this framework uses a refined modular design for functionalities and utilizes a collaborative approach between task management and the thread pool. The development and evaluation conducted on an actual vehicular testbed have confirmed that this framework significantly enhances the data processing capacity, stability and robustness of vehicular communications, which results in a significant increase of 41.62% in data processing speed and a substantial reduction of 22.68% in peak processor load, which is particularly suitable for ITS applications that require handling large data volume and demanding real-time performance.