Solving Urban Parking Inefficiency through Blockchain and SDN: From Formulation to Implementation

Rapid urbanization, increased vehicle ownership, and limited parking infrastructure have led to pervasive parking inefficiencies, adversely affecting urban mobility, energy consumption, and environmental sustainability. Current parking systems often suffer from scalability, fairness, and trust issues, especially in multi-provider environments. In this paper, we present a novel Blockchain-enhanced parking system integrated with Software-Defined Networking (SDN) that optimizes the allocation of parking resources in a decentralized and fair manner. We formulate parking allocation as a constrained linear optimization problem, with the objective of balancing the user distribution across parking lots while minimizing the overall load imbalance. To solve this NP-hard problem, we develop and evaluate multiple heuristic scheduling algorithms, including Local Search, Branch and Bound method. Extensive simulations demonstrate the effectiveness of the proposed system in different car arrival distributions and batch sizes, with the Local Search algorithm achieving the most consistent performance. Our system provides a robust, scalable, and fair smart parking solution, setting the foundation for future deployments in smart city infrastructure.