A distributed database consistency method for intelligent connected vehicle cloud control platform

Intelligent Connected Vehicle (ICV) cloud control platforms serve as the central hub of intelligent transportation systems, where the consistency guarantee of distributed databases is crucial for the safety and reliability of cooperative vehicle control. To address the critical issues of leader node performance bottlenecks, inefficient log synchronization, and excessive consistency check overhead in existing Raft algorithms under high-load data synchronization scenarios, this paper proposes an optimized Raft consensus algorithm. By incorporating segmented log synchronization, an anti-entropy mechanism, and a dynamic trust management model, the proposed solution achieves a read/write throughput of 184,000 QPS (44.9% improvement over standard Raft) while reducing read/write latency by 28.6% at 16MB data scale. Experimental results demonstrate that the improved Raft algorithm reduces log conflicts by 61.8% under high concurrency (60 threads), verifying its stability in high-load scenarios. This work provides a high-consistency, low-latency distributed storage solution for ICV cloud control platforms, facilitating their large-scale deployment in complex transportation scenarios.