Authors:
Sajal Chakraborty,Souritra Mandal,Subham Ghosh,Ankan Bhattacharya,Sankar Mukherjee,Biswa Mohan Acharya,Nabajyoti Medhi,DOI NO:
https://doi.org/10.26782/jmcms.2026.08.00003Keywords:
Blockchain,HIoT,Latency,Fog Computing,Micro and Macro latency.,Abstract
The Healthcare Internet of Things (HIoT) supports real-time monitoring and clinical decision-making through interconnected medical devices and sensors. Fog computing reduces communication delay by processing data near its source, while blockchain improves security, integrity, and decentralized trust. However, filtering, encryption, authentication, queueing, and consensus introduce additional latency, particularly in resource-constrained HIoT environments. Existing studies mainly address system-level delay, while micro-latency from local processing, hashing, memory access, and verification remains comparatively less explored. This study reviews latency-reduction approaches across the data filtering and encryption layers using a micro–macro perspective. A dependency-aware model links local processing with propagation, queueing, consensus and storage. Reported results are interpreted according to their architectural and evaluation conditions, while component-level analysis distinguishes isolated effects from coupled architectural improvements, showing that end-to-end latency arises from interactions across multiple processing stages.Refference:
I. A. A. Khan, A. A. Laghari, R. Alroobaea, A. M. Baqasah, M. Alsafyani, H. Alsufyani, and S. Ullah, “A lightweight scalable hybrid authentication framework for Internet of Medical Things (IoMT) using blockchain hyperledger consortium network with edge computing,” Scientific Reports, vol. 15, no. 1, p. 19856, 2025.
II. A. Ali, B. A. S. Al-Rimy, F. S. Alsubaei, A. A. Almazroi, and A. A. Almazroi, “HealthLock: Blockchain-based privacy preservation using homomorphic encryption in Internet of Things healthcare applications,” Sensors, vol. 23, no. 15, p. 6762, 2023.
III. A. Hashim, R. Rulaningtyas, and K. Chellappan, “Optimizing security and latency in blockchain-based health data management: A Hyperledger Fabric approach with multi-objective optimization,” Jurnal Kejuruteraan, vol. 37, no. 5, pp. 2469–2485, 2025.
IV. A. Shahidinejad and J. Abawajy, “An all-inclusive taxonomy and critical review of blockchain-assisted authentication and session key generation protocols for IoT,” ACM Computing Surveys, vol. 56, no. 7, pp. 1–38, 2024.
V. A. U. Rehman, N. Tariq, M. A. Jan, F. Khan, H. Song, and M. Ibrahim, “A blockchain-based hybrid model for IoMT-enabled intelligent healthcare system,” IEEE Transactions on Network Science and Engineering, vol. 11, no. 4, pp. 3512–3521, 2024.
VI. Bollineni, M. Sharma, A. Hazra, P. Kumari, S. Manipriya, and A. Tomar, “IoT for next-generation smart healthcare: A comprehensive survey,” IEEE Internet of Things Journal, vol. 12, no. 16, pp. 32616–32639, 2025.
VII. H. V. N. U. B. Murthy and M. Lawanya Shri, “An adaptive blockchain framework for federated IoMT with reinforcement learning-based consensus and resource forecasting,” Scientific Reports, 2026.
VIII. G. Niu, “A blockchain-based secure and privacy-preserving healthcare data management framework with SHA-256 and PoW consensus,” Informatica, vol. 49, no. 20, 2025.
IX. H. Gupta and P. Verma, “A survey on data security and latency frameworks in healthcare using blockchain,” in 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 1745–1750, 2024.
X. H. Taherdoost, “Blockchain-based Internet of Medical Things,” Applied Sciences, vol. 13, no. 3, p. 1287, 2023.
XI. J. Babatope, “Designing energy-efficient cryptographic modules for securing real-time data communication in embedded Internet of Things (IoT) devices,” International Research Journal of Modernization in Engineering, Technology and Science, vol. 7, no. 8, p. 1995, 2025.
XII. J. E. Abang, H. Takruri, R. Al-Zaidi, and M. Al-Khalidi, “Latency performance modelling in Hyperledger Fabric blockchain: Challenges and directions with an IoT perspective,” Internet of Things, vol. 26, p. 101217, 2024.
XIII. K. Koshikawa, J.-D. Kim, W.-J. Hwang, K. Nguyen, H. Sekiya, “Dual Perigee: Reducing Latency in IoT Blockchain through Efficient Peer Selection”, Proc. IEEE 99th Vehicular Technology Conference (VTC2024-Spring), pp. 1–5, 2024.
XIV. K. Koshikawa, Y. Su, J.-D. Kim, W.-J. Hwang, Z. Li, K. Nguyen, and H. Sekiya, “Impacts of overlay topologies and peer selection on latencies in IoT blockchain,” IEEE Transactions on Network and Service Management, vol. 23, pp. 1630–1646, 2025.
XV. Anjum, N. Kraiem, H. Min, A. K. Dutta, Y. I. Daradkeh, and S. Shahab, “Opportunistic access control scheme for enhancing IoT-enabled healthcare security using blockchain and machine learning,” Scientific Reports, vol. 15, no. 1, p. 7589, 2025.
XVI. A. Obaidat, M. Rawashdeh, M. Alja’afreh, M. Abouali, K. Thakur, and A. Karime, “Exploring IoT and blockchain: A comprehensive survey on security, integration strategies, applications and future research directions,” Big Data and Cognitive Computing, vol. 8, no. 12, p. 174, 2024.
XVII. Ejaz, T. Kumar, I. Kovacevic, M. Ylianttila, and E. Harjula, “Health-BlockEdge: Blockchain-edge framework for reliable low-latency digital healthcare applications,” Sensors, vol. 21, no. 7, p. 2502, 2021.
XVIII. Kumar, A. Kumar, S. Verma, P. Bhattacharya, D. Ghimire, S.-H. Kim, and A. S. S. Hosen, “Healthcare Internet of Things (H-IoT): Current trends, future prospects, applications, challenges and security issues,” Electronics, vol. 12, no. 9, p. 2050, 2023.
XIX. Q. Al-Tuma and M. K. Ibrahem, “Enhanced secure blockchain-edge-Internet of Things system for real-time healthcare monitoring,” International Journal of Intelligent Engineering and Systems, vol. 18, no. 10, pp. 494–514, 2025.
XX. Zhou, L. Zeng, Y. Han, P. Li, F. Long, D. Zhou, I. Beschastnikh, and M. Wu, “Mercury: Fast transaction broadcast in high performance blockchain systems,” in IEEE INFOCOM 2023 – IEEE Conference on Computer Communications, pp. 1–10, 2023.
XXI. N. Kaur, A. Mittal, U. K. Lilhore, S. Simaiya, S. Dalal, K. Saleem, and E. S. Ghith, “Securing fog computing in healthcare with a zero-trust approach and blockchain,” EURASIP Journal on Wireless Communications and Networking, vol. 2025, no. 1, p. 5, 2025.
XXII. N. M. Ali, Y. A. El Ghafar, and G. A. El Khayat, “Reducing latency and enhancing data security in healthcare IoT systems using fog computing,” in 2025 International Conference on Machine Intelligence and Smart Innovation (ICMISI), pp. 7–12, 2025.
XXIII. N. S. Al-Blihed, N. F. Al-Mufadi, N. T. Al-Harbi, I. A. Al-Omari, and M. A. Al-Hagery, “Blockchain and machine learning in the Internet of Things: A review of smart healthcare,” IAES International Journal of Artificial Intelligence, vol. 12, no. 3, pp. 995–1006, 2023.
XXIV. O. Cheikhrouhou, K. Mershad, F. Jamil, R. Mahmud, A. Koubaa, and S. R. Moosavi, “A lightweight blockchain and fog-enabled secure remote patient monitoring system,” Internet of Things, vol. 22, p. 100691, 2023.
XXV. P. Karthikeyan and K. Brindha, “FogChainFlow: On-off blockchain data management for optimizing IoT healthcare,” Cluster Computing, vol. 28, no. 16, p. 1011, 2025.
XXVI. R. R. Pai and B. Pandey, “Edge computing for healthcare IoT: Designing distributed data processing architectures for clinical devices,” in Proc. IEEE Int. Conf. on Compute, Control, Network & Photonics (ICCCNP), pp. 1–6, 2025.
XXVII. S. Akter, M. Tabassum, R. Sultana, and M. S. H. Bhuiyan, “Blockchain for real-time healthcare data acquisition: A systematic review of sensor network applications and challenges,” American Journal of Interdisciplinary Studies, vol. 6, no. 1, pp. 208–235, 2025.
XXVIII. S. Badri, S. U. Jan, D. M. Alghazzawi, S. Aldhaheri, and N. Pitropakis, “BIoMT: A blockchain-enabled healthcare architecture for information security in the Internet of Medical Things,” Computer Systems Science and Engineering, vol. 46, no. 3, pp. 3667–3684, 2023.
XXIX. S. Guan, Y. Cao, and Y. Zhang, “Blockchain-enhanced data privacy preservation and secure sharing scheme for healthcare IoT,” IEEE Internet of Things Journal, vol. 12, no. 5, pp. 5600–5614, 2025.
XXX. S. Lee, M. Kim, J. Lee, R.-H. Hsu, M.-S. Kim, and T. Q. S. Quek, “Facing latency of Hyperledger Fabric for blockchain-enabled IoT: Modeling and analyses,” IEEE Network, vol. 37, no. 6, pp. 232–239, 2023.
XXXI. S. Muthuvel, S. Priya, and K. Sampath Kumar, “Design of a multi-layered privacy-preserving architecture for secure medical data exchange in cloud environments,” Scientific Reports, vol. 16, no. 1, 2026.
XXXII. S. M. and V. K. Chattu, “A review of artificial intelligence, big data, and blockchain technology applications in medicine and global health,” Big Data and Cognitive Computing, vol. 5, no. 3, p. 41, 2021.
XXXIII. S. Ravisankar and R. Maheswar, “SecureEdge-MedChain: A post-quantum blockchain and federated learning framework for real-time predictive diagnostics in IoMT,” Sensors, vol. 25, no. 19, p. 5988, 2025.
XXXIV. T. E. Ali, F. I. Ali, P. Dakić, and A. D. Zoltan, “Trends, prospects, challenges and security in the healthcare Internet of Things,” Computing, vol. 107, no. 1, p. 28, 2025.
XXXV. U. Islam, M. N. Alatawi, A. Alqazzaz, S. Alamro, B. Shah, and F. Moreira, “A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience,” Scientific Reports, vol. 15, no. 1, p. 25655, 2025.
XXXVI. W. V. Solis, J. M. Parra-Ullauri, and A. Kertesz, “Exploring the synergy of fog computing, blockchain and federated learning for IoT applications: A systematic literature review,” IEEE Access, vol. 12, pp. 68015–68060, 2024.
XXXVII. Y. Singh, M. A. Jabbar, S. K. Shandilya, O. Vovk, and Y. Hnatiuk, “Exploring applications of blockchain in healthcare: Road map and future directions,” Frontiers in Public Health, vol. 11, p. 1229386, 2023.
XXXVIII. Y. Zhu, C. Hua, D. Zhong, and W. Xu, “Design of low-latency overlay protocol for blockchain delivery networks,” IEEE Wireless Communications and Networking Conference (WCNC), pp. 1182–1187, 2022.