Mrinal Kanti Mahato; Bikash Choudhury; Tanushree Garai; Sudip Kumar Adhikari; Himadri Nath Saha

Adaptive Context-Aware Replication Mechanism for Distributed IoT Environments

PDF (1885KB), PP.106-129

Views: 0 Downloads: 0

Author(s)

Mrinal Kanti Mahato ¹ Bikash Choudhury ^2,* Tanushree Garai ³ Sudip Kumar Adhikari ⁴ Himadri Nath Saha ⁵

1. Department of CS, Nistarini College, Purulia, 723101, India

2. Department of CSE, Ramkrishna Mahato Government Engineering College, Purulia, 723103, India

3. Department of CSE, Government College of Engineering & Ceramic Technology, Kolkata, 700010, India

4. Department of CSE, Kalyani Government Engineering College, Nadia, 741235, India

5. Department of Computer Science, Surendranath Evening College, Kolkata, 700009, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijcnis.2026.04.06

Received: 27 Jan. 2026 / Revised: 11 Mar. 2026 / Accepted: 22 Apr. 2026 / Published: 8 Aug. 2026

Index Terms

Service Replication, Internet of Things, Context-Aware, Proactive Sensing

Abstract

The rapid evolution of the Internet of Things (IoT), supported by the convergence of cloud, edge and mist computing layers, opens new avenues for delivering reliable and responsive services to distributed smart devices. However, ensuring efficient and adaptive service replication in such resource-constrained and dynamically changing IoT environments remains a significant challenge. To tackle this, we introduce Elastic Context-Aware Replication (ECAR), an intelligent replication strategy tailored for IoT systems. ECAR dynamically redistributes services across the IoT continuum by leveraging both physical and logical contextual information. Unlike traditional replication schemes, ECAR continuously adapts to real-time workload fluctuations and network conditions, ensuring low latency and efficient resource usage. ECAR’s effectiveness is demonstrated through a comparative evaluation involving diverse IoT deployment scenarios, including Cloud-Intensive Replication (CIR), Cloud-Edge-Intensive Replication (CEIR) and Cloud-Edge-Access-Intensive Replication (CEAIR), alongside two existing replication strategies, Group-Delay-Aware Replication (GDAR) and Combined Context-Aware Replication (CCA). The evaluation shows ECAR achieving up to 18% reduction in service drop rates, 82% improvement in allocation efficiency and 82% better resource utilization. These results underline ECAR’s effectiveness in supporting scalable, reliable and latency-aware service delivery for IoT deployments.

Cite This Paper

Mrinal Kanti Mahato, Bikash Choudhury, Tanushree Garai, Sudip Kumar Adhikari, Himadri Nath Saha, "Adaptive Context-Aware Replication Mechanism for Distributed IoT Environments", International Journal of Computer Network and Information Security(IJCNIS), Vol.18, No.4, pp. 106-129, 2026. DOI:10.5815/ijcnis.2026.04.06

Reference

[1]K. Cao, Y. Liu, G. Meng, and Q. Sun, "An Overview on Edge Computing Research," IEEE Access, vol. 8, pp. 85714–85728, 2020. doi: 10.1109/ACCESS.2020.2991734.
[2]R. Roman, J. Lopez, and M. Mambo, "Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges," Future Gener. Comput. Syst., vol. 78, pp. 680–698, Jan. 2018. doi: 10.1016/j.future.2016.11.009.
[3]L. Ni, J. Zhang, C. Jiang, C. Yan, and K. Yu, "Resource Allocation Strategy in Fog Computing Based on Priced Timed Petri Nets," IEEE Internet Things J., vol. 4, no. 5, pp. 1216–1228, Oct. 2017. doi: 10.1109/JIOT.2017.2709814.
[4]J. J. López Escobar, R. Díaz Redondo, and F. Gil-Castiñeira, "In-depth Analysis and Open Challenges of Mist Computing," J. Cloud Comput., vol. 11, no. 1, pp. 1–26, Nov. 2022. doi: 10.1186/s13677-022-00354-x.
[5]D. Guinard, V. Trifa, S. Karnouskos, P. Spiess, and D. Savio, "Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services," IEEE Trans. Serv. Comput., vol. 3, no. 3, pp. 223–235, Jul./Sep. 2010. doi: 10.1109/TSC.2010.3.
[6]J. Al-Jaroodi, N. Mohamed, and J. Aziz, "Service Oriented Middleware: Trends and Challenges," in Proc. 7th Int. Conf. Inf. Technol.: New Gener. (ITNG), 2010, pp. 974–979. doi: 10.1109/ITNG.2010.55.
[7]B. Cheng, D. Zhu, S. Zhao, and J. Chen, "Situation-Aware IoT Service Coordination Using the Event-Driven SOA Paradigm," IEEE Trans. Netw. Serv. Manag., vol. 13, no. 2, pp. 349–361, Jun. 2016. doi: 10.1109/TNSM.2016.2541171.
[8]S. Slimani, T. Hamrouni, and F. Ben Charrada, "Service-Oriented Replication Strategies for Improving Quality-of-Service in Cloud Computing: A Survey," Cluster Comput., vol. 24, no. 1, pp. 361–392, Mar. 2021. doi: 10.1007/s10586-020-03108-z.
[9]J. Ren, G. Yu, Y. He, and G. Y. Li, "Collaborative Cloud and Edge Computing for Latency Minimization," IEEE Trans. Veh. Technol., vol. 68, no. 5, pp. 5031–5044, May 2019. doi: 10.1109/TVT.2019.2904244.
[10]P. Rodriguez and E. W. Biersack, "Dynamic Parallel Access to Replicated Content in the Internet," IEEE/ACM Trans. Netw., vol. 10, no. 4, pp. 455–465, Aug. 2002. doi: 10.1109/TNET.2002.801413.
[11]H. Shen and G. Liu, "A Lightweight and Cooperative Multifactor Considered File Replication Method in Structured P2P Systems," IEEE Trans. Comput., vol. 62, no. 11, pp. 2115–2130, Nov. 2013. doi: 10.1109/TC.2012.104.
[12]N. B. Salah and N. Bellamine Ben Saoud, "IoT Data Placement in the Fog Infrastructure with Mobile Devices," in Proc. IEEE/ACM 21st Int. Symp. Cluster Cloud Internet Comput. (CCGrid), 2021, pp. 21–30. doi: 10.1109/CCGrid51090.2021.00012.
[13]S. He and X. H. Sun, "A Cost-Effective Distribution-Aware Data Replication Scheme for Parallel I/O Systems," IEEE Trans. Comput., vol. 67, no. 10, pp. 1374–1387, Oct. 2018. doi: 10.1109/TC.2018.2831689.
[14]D. M. Bui, S. Hussain, E.-N. Huh, and S. Lee, "Adaptive Replication Management in HDFS Based on Supervised Learning," IEEE Trans. Knowl. Data Eng., vol. 28, no. 6, pp. 1369–1382, Jun. 2016. doi: 10.1109/TKDE.2016.2523510.
[15]C. Berger, H. P. Reiser, J. Sousa, and A. Bessani, "AWARE: Adaptive Wide-Area Replication for Fast and Resilient Byzantine Consensus," IEEE Trans. Dependable Secure Comput., vol. 19, no. 3, pp. 1605–1620, May/Jun. 2022. doi: 10.1109/TDSC.2020.3030605.
[16]S. A. Mohamed, S. Sorour, and H. S. Hassanein, "Group Delay-Aware Scalable Mobile Edge Computing Using Service Replication," IEEE Trans. Veh. Technol., vol. 71, no. 11, pp. 11911–11920, Nov. 2022. doi: 10.1109/TVT.2022.3193887.
[17]H. Shen, G. Liu, and H. Chandler, "Swarm Intelligence Based File Replication and Consistency Maintenance in Structured P2P File Sharing Systems," IEEE Trans. Comput., vol. 64, no. 10, pp. 2953–2967, Oct. 2015. doi: 10.1109/TC.2015.2389845.
[18]P. T. Wojciechowski, T. Kobus, and M. Kokocinski, "State-Machine and Deferred-Update Replication: Analysis and Comparison," IEEE Trans. Parallel Distrib. Syst., vol. 28, no. 3, pp. 891–904, Mar. 2017. doi: 10.1109/TPDS.2016.2590422.
[19]S. Verma, A. K. Yadav, D. Motwani, R. S. Raw, and H. K. Singh, "An Efficient Data Replication and Load Balancing Technique for Fog Computing Environment," in Proc. 3rd Int. Conf. Comput. Sustainable Global Dev. (INDIACom), 2016, pp. 2888–2895.
[20]Y.J. Yu, T.C. Chiu, A.-C. Pang, M.-F. Chen, and J. Liu, "Virtual Machine Placement for Backhaul Traffic Minimization in Fog Radio Access Networks," in Proc. IEEE Int. Conf. Commun. (ICC), 2017, pp. 1–7. doi: 10.1109/ICC.2017.7996500.
[21]L. Yang, A. Zhou, X. Ma, Y. Zhang, and S. Wang, "Reliability-Aware Task Replication for Mobile Edge Computing," IEEE Internet Things J., vol. 11, no. 14, pp. 24846–24857, Jul. 2024. doi: 10.1109/JIOT.2024.3388156.
[22]B. Choudhury, S. Choudhury, and A. Dutta, "A Proactive Context-Aware Service Replication Scheme for Adhoc IoT Scenarios," IEEE Trans. Netw. Serv. Manag., vol. 16, no. 4, pp. 1797–1811, Dec. 2019. doi: 10.1109/TNSM.2019.2928698.
[23]M. Polverini, J. Galan-Jimenez, F. G. Lavacca, A. Cianfrani, and V. Eramo, "Improving Dynamic Service Function Chaining Classification in NFV/SDN Networks Through the Offloading Concept," Comput. Netw., vol. 182, p. 107480, Dec. 2020. doi: 10.1016/j.comnet.2020.107480.
[24]M. A. Ahmed, M. H. Khafagy, M. E. Shaheen, and M. R. Kaseb, "Dynamic Replication Policy on HDFS Based on Machine Learning Clustering," IEEE Access, vol. 11, pp. 18551–18559, 2023. doi: 10.1109/ACCESS.2023.3247190.
[25]F. Arar, R. Mokadem, and D. E. Zegour, "Towards Using Reinforcement Learning for Scaling and Data Replication in Cloud Systems," in Proc. Doctoral Conf. Comput. Sci. (ADCCS), Algiers, Algeria, May 2024.
[26]A. Najjar et al., "Towards Designing an Energy Aware Data Replication Strategy for Cloud Systems Using Reinforcement Learning," arXiv preprint arXiv:2507.18459, 2025.
[27]A. Murimi , "How Machine Learning-Data Driven Replication Strategies Enhance Fault Tolerance in Large-Scale Distributed Systems," arXiv preprint arXiv:2511.11749, 2025.
[28]L. Zhai, Z. Lu, J. Sun, and X. Li, "Joint Task Offloading and Computing Resource Allocation with DQN for Task-Dependency in Multi-access Edge Computing," Comput. Netw., vol. 263, p. 111222, Mar. 2025. doi: 10.1016/j.comnet.2025.111222.
[29]L. Zhai, P. Zhao, K. Xue, Y. Li, and C. Cheng, "Task Offloading and Multi-Cache Placement in Multi-access Mobile Edge Computing," Comput. Netw., vol. 258, p. 111030, 2025. doi: 10.1016/j.comnet.2024.111030.
[30]J. Zhang, Y. Peng, F. Zhou, F. Lei, W. Li, and X. Qiu, "Resource and Delay Aware Fine-Grained Service Offloading in Collaborative Edge Computing," Comput. Netw., vol. 218, p. 109383, Dec. 2022. doi: 10.1016/j.comnet.2022.109383.
[31]Hanen Tlich et al, "A Clustering-Aware and Multi-Feature Replication Strategy for Efficient Storage in HDFS," Procedia Comput. Sci. (KES 2025), Amsterdam: Elsevier, 2025.
[32]Nour-Eddine Bakni and Ismail Assayad, "Smart Data Placement Strategy in Heterogeneous Hadoop," HighTech Innov. J., 2025. doi: 10.28991/HIJ-2025-06-01.
[33]G. Manogaran et al., "Machine Learning Assisted Information Management Scheme in Service Concentrated IoT," IEEE Trans. Ind. Informat., vol. 17, no. 4, pp. 2871–2879, Apr. 2021. doi: 10.1109/TII.2020.3012759.
[34]T. Bilen and B. Canberk, "Handover-Aware Content Replication for Mobile-CDN," IEEE Netw. Lett., vol. 1, no. 1, pp. 10–13, Mar. 2019. doi: 10.1109/LNET.2018.2873982.
[35]S. Zhou, Y. Sun, Z. Jiang, and Z. Niu, "Exploiting Moving Intelligence: Delay-Optimized Computation Offloading in Vehicular Fog Networks," IEEE Commun. Mag., vol. 57, no. 5, pp. 49–55, May 2019. doi: 10.1109/MCOM.2019.1800230.
[36]I. M. Amer, S. M. A. Oteafy, and H. S. Hassanein, "Task Replication in Unreliable Edge Networks," in Proc. IEEE 47th Conf. Local Comput. Netw. (LCN), 2022, pp. 173–180. doi: 10.1109/LCN53696.2022.9843613.
[37]J. Khan, C. Westphal, and Y. Ghamri-Doudane, "A Content-Based Centrality Metric for Collaborative Caching in Information-Centric Fogs," May 2017.
[38]K. C. Mondal, "Algorithms for Data Mining and Bio-informatics," Ph.D. dissertation, Universite Nice Sophia Antipolis, Nice, France, Jul. 2013.
[39]K. Macarthur, "Multi-Agent Coordination for Dynamic Decentralised Task Allocation," Ph.D. dissertation, Univ. of Southampton, Southampton, UK, 2011.
[40]S. M. Aji and R. J. McEliece, "The Generalized Distributive Law," IEEE Trans. Inf. Theory, vol. 46, no. 2, pp. 325–343, Mar. 2000.
[41]S. Bistarelli, R. Gennari, and F. Rossi, "Constraint Propagation for Soft Constraints: Generalization and Termination Conditions," in Proc. 6th Int. Conf. Princ. Pract. Constraint Program. (CP), 2000, pp. 83–97.
[42]N. Mohamed, J. Al-Jaroodi, I. Jawhar, S. Lazarova-Molnar, and S. Mahmoud, "SmartCityWare: A Service-Oriented Middleware for Cloud and Fog Enabled Smart City Services," IEEE Access, vol. 5, pp. 17576–17588, 2017. doi: 10.1109/ACCESS.2017.2731382.

International Journal of Computer Network and Information Security (IJCNIS)