5G Software Defined Vehicular Networks (1702.03675v1)

Abstract: With the emerging of the fifth generation (5G) mobile communication systems and software defined networks, not only the performance of vehicular networks could be improved but also new applications of vehicular networks are required by future vehicles, e.g., pilotless vehicles. To meet requirements from intelligent transportation systems, a new vehicular network architecture integrated with 5G mobile communication technologies and software defined network is proposed in this paper. Moreover, fog cells have been proposed to flexibly cover vehicles and avoid frequently handover between vehicles and road side units (RSUs). Based on the proposed 5G software defined vehicular networks, the transmission delay and throughput are analyzed and compared. Simulation results indicate that there exist a minimum transmission delay of 5G software defined vehicular networks considering different vehicle densities. Moreover, the throughput of fog cells in 5G software defined vehicular networks is better than the throughput of traditional transportation management systems.

• The paper presents a novel 5G vehicular network framework integrating SDN, cloud, and fog computing to reduce transmission delays for intelligent transportation systems.
• It introduces a fog cell architecture that minimizes handovers and adaptively allocates bandwidth in dynamic vehicle environments.
• Performance simulations reveal that optimal vehicle density minimizes delay and significantly enhances throughput compared to traditional systems.

Overview of 5G Software Defined Vehicular Networks

The paper "5G Software Defined Vehicular Networks," authored by Xiaohu Ge, Zipeng Li, and Shikuan Li, presents a novel architectural framework for integrating 5G mobile communication technologies with software-defined networks (SDNs) and fog computing to address critical demands from emerging intelligent transportation systems (ITS), particularly pilotless vehicles. The authors introduce a comprehensive design for vehicular networks, underpinning it with analytical investigations of transmission delay and throughput to highlight the advantages over existing vehicular communication infrastructures.

Core Contributions

This research delivers a structured approach to enhancing vehicular communications via three principal propositions:

1. Architectural Integration: The proposed 5G software-defined vehicular network comprises three logical planes—application, control, and data. These planes ensure that control and data operations are decoupled, fostering improved scalability and flexibility. This integration utilizes SDN, cloud computing, and fog computing, thereby enabling efficient management and allocation of wireless resources.
2. Fog Cell Architecture: A pivotal innovation is the fog cell structure which minimizes handovers between road side units (RSUs) and vehicles, effectively alleviating potential communication disruptions. Fog cells allow adaptive bandwidth allocation to optimize wireless communications among vehicles in dynamic mobility scenarios.
3. Performance Evaluation: Detailed simulations highlight that transmission delay in fog cells exhibits a minimum value under varying vehicle densities. Additionally, throughput analyses reveal that the fog cell strategy outperforms traditional transport management systems significantly.

Analytical Insights

The paper provides a meticulous assessment of vehicular network dynamics concerning transmission delay and throughput metrics. Notably, simulation results reveal that optimal vehicle density exists, minimizing transmission delays. This is crucial for vehicular communication where latency must remain exceedingly low, especially for ITS applications requiring real-time data exchange.

Throughput results reinforce the superiority of the proposed fog cell architecture over conventional systems in scenarios of varying vehicle counts. These advancements suggest a robust path forward in achieving high-efficiency vehicular communications required for pilotless vehicle systems.

Implications and Future Directions

The implications of this research are manifold for both practical and theoretical domains. Practically, the proposed architecture offers a viable solution to managing the immense scale and complexity expected in future vehicular networks, enhancing both connectivity and data handling amidst increasing vehicle automation and traffic density.

Theoretically, the paper establishes a foundation for future explorations into adaptive network configurations leveraging fog computing and SDNs. These aspects could catalyze further investigations into dynamically optimized vehicular networks, possibly integrating AI-driven resource allocation strategies to enhance network self-organization and decision-making capabilities.

While the paper successfully addresses several key challenges associated with vehicular networking, ongoing work remains necessary to tackle associated issues such as network scalability, interoperability, and low-latency decision-making under diverse operational conditions. Future research could explore AI-driven adaptive control mechanisms within the fog cell architecture and examine real-world deployment scenarios.

In summary, the proposed 5G software-defined vehicular network framework embodies a significant stride in aligning network innovations with emerging vehicular communication needs. This work serves as a valuable guidepost for advancing vehicular network technologies in tandem with the evolving landscape of smart transportation systems.