SLDSM: sparse location data sharing model based on VN-PBFT for IoV
Qiuli Yan, Jun Wang, Yi Xin Zhou, Dejun Wang · 2025
Location data sharing is a key foundational service for intelligent transportation. However, in sparse location data scenarios, existing data sharing solutions based on Practical Byzantine Fault Tolerance (PBFT) consensus face high latency and even consensus failure issues. In response to this issue, we propose a sparse location data sharing model based on virtual node PBFT consensus, which utilizes virtual nodes to complete node clustering and improves the real-time performance of the model. Simulation experiment results show that compared with PBFT and its improved algorithm Optimized Byzantine Consensus Parallelism Scheme (ParBFT), the average consensus latency of Virtual Nodes-Practical Byzantine Fault Tolerance (VN-PBFT) algorithm is increased by 42.91% and 23.48% respectively.