Benchmarking Consensus Protocols for High-Performance Permissioned Blockchain Systems

Blockchain applications rely on consensus protocols to maintain security, integrity, and coordination in decentralized environments while balancing performance, scalability, and resource cost. This study presents a comparative evaluation of four Hyperledger Besu consensus algorithms, namely Ethash, Clique, QBFT, and IBFT 2.0, executed under identical hardware, network topology, and genesis configurations to quantify latency, throughput, and system overhead. A distributed burst workload is employed to simulate high-intensity transaction conditions. Within this framework, sender and receiver accounts are automatically generated and funded, and 5000 transactions are submitted in parallel. Locally recorded millisecond-precision submission timestamps are aligned with second-resolution on-chain block timestamps to compute inclusion latency percentiles and end-to-end burst throughput. System and blockchain metrics, including block interval, transaction pool backlog, and block creation time, are collected through Prometheus over defined intervals and synchronized with transaction traces for time-series analysis. Across ten repeated runs per protocol, Clique achieves the lowest latency of approximately two seconds and the highest throughput of approximately 190 transactions per second. QBFT and IBFT 2.0 demonstrate stable and periodic performance near 110 transactions per second with low variance. In contrast, Ethash exhibits highly variable, high-variance and strongly right-skewed latencies, minimal throughput, and substantially higher energy consumption and disk input/output peaks. CPU, memory, and network traffic profiles further expose distinct operational trade-offs relevant to deployment scenarios. Statistical analyses using the Kruskal–Wallis and Dunn’s post hoc tests confirm significant differences among the protocols with large effect sizes. The proposed framework provides a rigorous and systematically documented methodology for comparative consensus performance evaluation in permissioned blockchain environments.