🤖 AI Summary
In highly dynamic multimodal transportation environments, conventional centralized control architectures struggle to meet the stringent requirements of low latency, high reliability, and scalability in communication. This work proposes a hierarchical distributed architecture that integrates Software-Defined Networking (SDN) with Multi-access Edge Computing (MEC), combining regional coordination with edge autonomy to enable local failover and adaptive interface management, thereby eliminating dependence on a central node. Experimental results demonstrate that the control-plane communication and flow establishment latency between the designed edge SDN controllers and Pods are significantly lower than those of existing approaches, confirming the proposed architecture’s superior efficiency and practicality.
📝 Abstract
Future multimodal transportation systems require reliable, low-latency communication infrastructures to coordinate autonomous vehicles and moving infrastructure across rail and road networks. Traditional centralized control architectures struggle to meet these requirements in highly dynamic environments due to increased latency, limited scalability, and poor adaptability to changing network conditions. To address this, we propose a distributed communication architecture integrating Software-Defined Networking (SDN) and Multi-Access Edge Computing (MEC), that can create a flexible, programmable and lowlatency network. Results show controller communication and flow setup latency between edge SDN controllers and Pods are lower than reported in literature. The framework uses hierarchical control with regional and edge controllers to support low-latency interface management and edge autonomy. Operational workflows and control logic are defined as representative scenarios. The architecture combines regional policy coordination with edge-level autonomy, enabling local failover and adaptive interface management without central dependency.