Adaptive Practical Byzantine Fault Tolerance with Dynamic Checkpointing

Practical Byzantine Fault Tolerance (PBFT) is a widely used consensus algorithm in distributed systems, offering robustness against malicious or faulty nodes. However, traditional PBFT implementations suffer from inefficiencies due to static checkpointing mechanisms, which lead to unnecessary computational overhead, reduced scalability, and increased latency. This paper introduces Adaptive PBFT with Dynamic Checkpointing, an enhanced approach that dynamically adjusts checkpoint intervals based on real-time system metrics such as transaction throughput, system load, network latency, and fault detection rate. By optimizing checkpoint frequency, the proposed method significantly improves PBFT's efficiency, reducing resource consumption while maintaining safety and liveness guarantees. Experimental results demonstrate a 30% increase in throughput, a 25% reduction in latency, and a 40% decrease in CPU utilization compared to static PBFT. These improvements make Adaptive PBFT more suitable for modern, large-scale distributed applications, addressing the limitations of traditional checkpointing strategies.