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By: Kazi Kutubuddin Sayyad Liyakat.
Professor and Head, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India
The relentless proliferation of Internet of Things maneuvers generates colossal volumes of data at the network edge, straining traditional cloud-centric paradigms with inherent limitations in latency, bandwidth, resilience, and privacy. This necessitates a paradigm shift towards distributed intelligence. Fog Computing arises as a pivotal architectural paradigm, extending computational, storage, and networking capabilities closer to the data source, thereby mitigating latency, reducing bandwidth consumption, and enhancing real-time processing capabilities for critical IoT applications. This paper delves into the foundational architectureof Fog Computing, dissecting its intricate layering from diverse edge devices (sensors, actuators, and gateways) through intermediate Fog nodes (routers, switches, and micro-data centers) to the overarching cloud hierarchy. We analyze key design principles, including geographical distribution, heterogeneity, virtualization, and the interplay between local and global intelligence. Furthermore, we examine critical considerations for its effective deployment in diverse IoT verticals, addressing challenges such as dynamic resource orchestration, energy efficiency, interoperability, robust security protocols across heterogeneous environments, and the need for standardized management frameworks. By exploring both the theoretical underpinnings and practical implications, this work underscores Fog Computing’s transformative potential to unlock new frontiers in intelligent, responsive, and resilient IoT ecosystems, paving the way for truly autonomous and data-driven decision-making at the edge.
Fog computing, Internet of Things (IoT), architecture and deployment, management, geographical distribution, intrusion detection systems
Citation:
Refrences:
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