HARNES: Heuristic Algorithm for Routing and Network Efficiency Using SDN in Intelligent Transportation Systems

In this paper, we introduce <tex-math notation="LaTeX">$HARNES$ </tex-math>, a heuristic and Software-Defined Networking (SDN)-enabled routing framework for dynamic vehicular networks. The framework enhances classical search algorithms by developing cluster-based extensions of <tex-math notation="LaTeX">Theta* </tex-math> and <tex-math notation="LaTeX">D* </tex-math>-Lite, which minimize computational overhead through localized decision-making and line-of-sight (LOS) optimization. By deploying <tex-math notation="LaTeX">$SDN$ </tex-math> controllers at roadside units (RSUs), <tex-math notation="LaTeX">$HARNES$ </tex-math> enables centralized coordination among clusters, thereby improving adaptability and scalability in large-scale networks. The proposed approach is evaluated against EG-Dijkstra (Evolving-Graph Dijkstra) and <tex-math notation="LaTeX">A* </tex-math> on grid-based vehicular topologies using six performance metrics: computation time, discovery messages, path length, expanded nodes, average degree of expanded nodes, and path optimality ratio. Simulation results demonstrate that the cluster-based <tex-math notation="LaTeX">Theta* </tex-math> achieves up to 42% reduction in computation time, 88% fewer discovery messages, and 47% fewer expanded nodes, while maintaining near-optimal path quality within 3.1% of optimality. Additional comparison with the original non-clustered <tex-math notation="LaTeX">Theta* </tex-math> and <tex-math notation="LaTeX">D* </tex-math>-Lite further confirms the effectiveness of the proposed cluster-based design. These findings highlight the potential of <tex-math notation="LaTeX">$HARNES$ </tex-math> as a low-latency, scalable, and SDN-compatible routing solution for real-time intelligent transportation systems.