International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Edge–Cloud Hybrid Architecture for IoT Systems

Author(s) Eeshan Sharma, Dimpy Singh, Anuj Saini
Country India
Abstract Edge–Cloud Hybrid Architecture has emerged as a transformative computing paradigm for modern Internet of Things (IoT) systems. With billions of interconnected devices generating massive amounts of real-time data, traditional cloud centric systems struggle with latency, bandwidth overload, and reliance on stable network connectivity. Hybrid architectures integrate edge intelligence for real-time decision-making with cloud infrastructure for global analytics, storage, and large-scale machine learning. This paper explores the evolution of hybrid IoT
models from basic device-to-cloud systems to advanced, multi layer edge–cloud frameworks. We present a detailed architectural analysis, practical system design, resource requirements, and a structured implementation pipeline adaptable for research and industry. Performance trade-offs involving latency, accuracy, energy consumption, and network overhead are analyzed with
mathematical models and experimental observations. Further more, we outline modern optimization strategies including edge inference, event-driven data reduction, and adaptive workload balancing. The study concludes by identifying emerging research directions such as federated edge learning, secure IoT
orchestration, and intelligent workload autonomics for large-scale deployments.
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-31
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62246
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E-ISSN 2582-2160
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