Performance Benchmarking of Hyperledger Fabric on Heterogeneous Hardware for IoT Applications

Authors

DOI:

https://doi.org/10.31436/iiumej.v26i3.3610

Keywords:

Hyperledger Fabric, Hyperledger Caliper, Internet of Things (IoT), Performance Analysis, IoT-Enabled Blockchain

Abstract

Hyperledger Fabric (HLF), a widely used open-source private blockchain, has garnered attention for its ability to enable blockchain in Internet of Things (IoT) applications. Embedding HLF nodes within IoT devices enables smart contract integration for secure and automated communications, thereby reducing reliance on intermediaries. However, resource-constrained IoT devices often face challenges with complex operations due to their limited processing power. While HLF deployment on single-board computers (SBCs) like Raspberry Pi has been explored, comprehensive performance evaluations across diverse hardware setups in a heterogeneous blockchain network are limited. This study benchmarks HLF performance on a network comprising SBCs with ARM architectures (Cortex-A72 and Cortex-A76) and laptops with Intel Core i7 and Intel Celeron processors. Using Hyperledger Caliper, key performance metrics, including throughput, latency, CPU usage, and memory consumption, were measured. Results show that high-throughput applications are best supported by high-end processors capable of handling multiple clients, achieving up to 1,148.3 TPS. In contrast, SBCs efficiently handle moderate transaction loads from single clients with minimal latency increases. These findings demonstrate the adaptability of HLF across varied hardware configurations, provided a proper network architecture setup, supporting its deployment in diverse IoT environments.

ABSTRAK:  Fabrik hiperlejer (Hyperledger Fabric, HLF), iaitu rantaian blok peribadi sumber terbuka yang digunakan secara meluas, telah mendapat perhatian kerana keupayaannya dalam memacu blok rantaian dalam aplikasi Internet of Things (IoT). Penyepaduan nod HLF ke dalam peranti IoT membolehkan penggunaan kontrak pintar bagi komunikasi selamat dan automatik, seterusnya mengurangkan kebergantungan kepada pihak ketiga. Namun, peranti IoT yang memiliki sumber terhad sering menghadapi cabaran dalam melaksanakan operasi kompleks disebabkan oleh kuasa pemprosesannya yang terhad. Walaupun penerapan nod HLF pada komputer papan tunggal (SBC) seperti Raspberry Pi telah dikaji, penilaian prestasi yang komprehensif merangkumi pelbagai konfigurasi perkakasan dalam blok rantaian heterogen masih terhad. Kajian ini merupakan penanda aras prestasi HLF pada rangkaian yang terdiri daripada SBC berasaskan seni bina ARM (Cortex-A72 dan Cortex-A76) serta komputer riba berprosesor Intel Core i7 dan Intel Celeron. Mengguna pakai Hyperledger Caliper, metrik prestasi utama seperti kadar penghantaran, masa tindak balas, penggunaan CPU, dan penggunaan memori telah diukur. Dapatan kajian menunjukkan bahawa kadar aplikasi penghantaran tertinggi, paling sesuai disokong oleh pemproses berprestasi tinggi yang mampu mengendalikan pelbagai klien, mencapai sehingga 1,148.3 TPS. Sementara itu, SBC berupaya mengendalikan beban transaksi sederhana daripada klien tunggal dengan peningkatan masa tindak balas yang minima. Penemuan ini menunjukkan kebolehsesuaian HLF merentasi pelbagai konfigurasi perkakasan, dengan syarat rangkaian yang sesuai disediakan, sekaligus menyokong pelaksanaannya dalam persekitaran IoT yang pelbagai.

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Author Biographies

Muhammad Muaz Zulkarnain, International Islamic University Malaysia

Muhammad Muaz Zulkarnain is a Master’s student at the Kulliyyah of Engineering (KOE), International Islamic University Malaysia (IIUM). His research focuses on blockchain technology, Internet of Things (IoT), and distributed ledger systems, with a particular interest in optimizing blockchain performance for resource-constrained environments. He has been actively involved in benchmarking Hyperledger Fabric (HLF) for IoT applications, exploring its deployment on heterogeneous hardware architectures.

He was also involved in a collaborative project with Petronas, where he played a role in developing a blockchain-based system for carbon offset tokenization, aimed at enhancing transparency and efficiency in carbon credit transactions. His expertise in blockchain performance optimization has allowed him to contribute valuable insights to both academic research and industry applications.

Anis Nurashikin Nordin, International Islamic University Malaysia

Professor Dr. Anis Nurashikin Nordin is a Microelectronics Professor and researcher at the Department of Electrical and Computer Engineering, International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia. She obtained her B. Eng. in Computer Engineering from IIUM and both her MSc and Doctor of Science in Microelectronics and VLSI from The George Washington University, Washington DC in 2003 and 2008 respectively. She has been teaching courses in Electronics Engineering since 2003. She has been awarded IEEE Senior Member. She has won IIUM’s Most Promising Researcher Award in 2010 and IIUM’s Most Outstanding Researcher Award in 2014. She has extensive international collaborative networks and has served as an invited researcher for Linkoping University, Sweden, City College of New York.

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Published

2025-09-09

How to Cite

Zulkarnain, M. M., Ramli, N., & Nordin, A. N. (2025). Performance Benchmarking of Hyperledger Fabric on Heterogeneous Hardware for IoT Applications. IIUM Engineering Journal, 26(3), 156–170. https://doi.org/10.31436/iiumej.v26i3.3610

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Section

Electrical, Computer and Communications Engineering

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