An Efficient and Scalable Byzantine Fault Tolerant Consensus for Vehicular Networks

Vehicular networks represent a new distributed system paradigm that requires robust fault tolerance to ensure reliable operation. As a burgeoning area of research, the scalability and optimization of consensus mechanisms for these networks are critical. Traditional Byzantine Fault Tolerant (BFT) algorithms like PBFT are not inherently optimized for the localized needs of vehicular networks, suffering from scalability issues due to their global nature and high messaging complexity. In response, we introduce a two-tiered consensus framework that refines PBFT for the specific context of vehicular networks. By organizing nodes into clusters based on geographic proximity, our approach reduces messaging complexity from $O(n^{2})$ to $O(n^{1.5})$, significantly improving scalability. The framework distinguishes between local and global state transitions, adding two phases to the PBFT protocol to manage these efficiently. This tailored consensus process aligns with the localized communication patterns of vehicular networks, enhancing both efficiency and scalability. The framework addresses the critical challenges of traditional BFT algorithms in vehicular networks, offering a solution that is both scalable and resilient. It is a step toward enabling vehicular networks to fulfil their potential as a reliable component of modern distributed systems.