Performance Benchmarking of Hyperledger Fabric on Heterogeneous Hardware for IoT Applications
DOI:
https://doi.org/10.31436/iiumej.v26i3.3610Keywords:
Hyperledger Fabric, Hyperledger Caliper, Internet of Things (IoT), Performance Analysis, IoT-Enabled BlockchainAbstract
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.
Downloads
Metrics
References
Laroui M, Nour B, Moungla H, Cherif MA, Afifi H, Guizani M. (2021). Edge and fog computing for IoT: A survey on current research activities & future directions. Computer Communications, 180, 210-231.
Maraveas C, Piromalis D, Arvanitis KG, Bartzanas T, Loukatos D. (2022). Applications of IoT for optimized greenhouse environment and resources management. Computers and Electronics in Agriculture, 198, 106993.
Kumar NM, Chand AA, Malvoni M, Prasad KA, Mamun KA, Islam FR, Chopra SS. (2020). Distributed energy resources and the application of AI, IoT, and blockchain in smart grids. Energies, 13(21), 5739.
Mathur S, Kalla A, Gür G, Bohra MK, Liyanage M. (2023). A survey on role of blockchain for IoT: Applications and technical aspects. Computer Networks, 227, 109726.
Makhdoom I, Abolhasan M, Abbas H, Ni W. (2019). Blockchain's adoption in IoT: The challenges, and a way forward. Journal of Network and Computer Applications, 125, 251-279.
Ashley MJ, Johnson MS. (2018). Establishing a secure, transparent, and autonomous blockchain of custody for renewable energy credits and carbon credits. IEEE Engineering Management Review, 46(4), 100-102.
Anand P, Singh Y, Selwal A, Alazab M, Tanwar S, Kumar N. (2020). IoT vulnerability assessment for sustainable computing: Threats, current solutions, and open challenges. IEEE Access, 8, 168825-168853.
Siwakoti YR, Bhurtel M, Rawat DB, Oest A, Johnson RC. (2023). Advances in IoT security: Vulnerabilities, enabled criminal services, attacks, and countermeasures. IEEE Internet of Things Journal, 10(13), 11224-11239.
Sharma PK, Kumar N, Park JH. (2020). Blockchain technology toward green IoT: Opportunities and challenges. IEEE Network, 34(4), 263-269.
Honar PH, Rashid MA, Alam F, Demidenko S. (2022). Experimental performance analysis of a scalable distributed hyperledger fabric for a large-scale IoT testbed. Sensors, 22(13), 4868.
Kaushal RK, Kumar N. (2024, March). Exploring hyperledger caliper benchmarking tool to measure the performance of blockchain based solutions. In 2024 11th international conference on reliability, infocom technologies and optimization (trends and future directions)(ICRITO) (pp. 1-6). IEEE.
Introduction - Hyperledger Fabric Docs main documentation. [https://hyperledger-fabric.readthedocs.io/en/release-2.5/whatis.html]
Introduction - Hyperledger Caliper. [https://hyperledger-caliper.github.io/caliper/0.6.0/]
Ucbas Y, Eleyan A, Hammoudeh M, Alohaly M. (2023). Performance and scalability analysis of ethereum and hyperledger fabric. IEEE Access, 11, 67156-67167.
Guggenberger T, Sedlmeir J, Fridgen G, Luckow A. (2022). An in-depth investigation of the performance characteristics of Hyperledger Fabric. Computers & Industrial Engineering, 173, 108716.
Wang C, Chu X. (2020, November). Performance characterization and bottleneck analysis of hyperledger fabric. In 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS) (pp. 1281-1286). IEEE.
Alexandridis A, Al-Sumaidaee G, Zilic Z, Jeon G, Wang J. (2023). An iot ecosystem platform for the evaluation of blockchain feasibility. IEEE Internet of Things Journal, 10(24), 21515-21527.
Honar PH, Rashid M, Alam F, Demidenko S. (2021). Hyperledger fabric blockchain for securing the edge internet of things. Sensors, 21(2), 359.
Iftekhar A, Cui X, Tao Q, Zheng C. (2021). Hyperledger fabric access control system for internet of things layer in blockchain-based applications. Entropy, 23(8), 1054.
Eghmazi A, Ataei M, Landry RJ, Chevrette G. (2024). Enhancing IoT data security: Using the blockchain to boost data integrity and privacy. IoT, 5(1), 20-34.
Xu X, Sun G, Luo L, Cao H, Yu H, Vasilakos AV. (2021). Latency performance modeling and analysis for hyperledger fabric blockchain network. Information Processing & Management, 58(1), 102436.
Khan D, Jung LT, Hashmani MA, Cheong MK. (2022). Empirical performance analysis of hyperledger LTS for small and medium enterprises. Sensors, 22(3), 915.
Foschini L, Gavagna A, Martuscelli G, Montanari R. (2020, June). Hyperledger fabric blockchain: Chaincode performance analysis. In ICC 2020-2020 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.
Alamsyah A, Hakim N, Hendayani R. (2022). Blockchain-based traceability system to support the Indonesian halal supply chain ecosystem. Economies, 10(6), 134.
Song S, Lu J, Zhao H, Wang W, Shi C, Luo R. (2022, November). Traceability of Product Supply Chain Based on Hyperledger Fabric. In Proceedings of the 4th International Conference on Advanced Information Science and System (pp. 1-6).
PassMark CPU Benchmarks - CPU Test Information. [https://www.cpubenchmark.net/cpu_test_info.html]
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 IIUM Press

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.








