Empirical Performance Analysis of Hyperledger Fabric Blockchain Network for Healthcare - Shampa Rani Das; NZ Jhanjhi; Farzeen Ashfaq; Husham M. Ahmed; Azeem Khan (Malikussaleh University, Aceh, Indonesia, 2025)
The most prevalent blockchain-enabled systems have several apparent advantages, but scaling remains a technical difficulty that results in performance deficiencies in latency and throughput. The foremost concern is that a thorough performance analysis is required to determine their viability and efficiency. The prospective impact of transaction delay on blockchain networks is an acute issue for e-healthcare-related services since it can jeopardize the patient’s life safety. A benchmarking tool Hyperledger Caliper is utilized to measure performance parameters in the Hyperledger Fabric network. The effects of workload fluctuation in 6 rounds with up to 3000 Transactions Per Second (TPS) are demonstrated when four organizations are put up in the network. Significant findings include a noteworthy decrease of 27.11% in open latency and 26.27% in query latency, and an increase of 3.13% in query throughput and 3.44% in open throughput demonstrating enhancements in adaptability and operational efficiency over the recent existing approaches proposed. It demonstrates an ongoing increase in CPU and memory consumption, peaking at 5.49% and 528.23 MB for 3000 TPS, respectively. Inbound and outbound traffic indicate relatively even utilization, with variations falling within a moderate range.