In the rapidly evolving landscape of the Internet of Things (IoT), the need for efficient data processing and management is paramount. Fog computing, with its decentralized approach, offers a promising solution to overcome the limitations of traditional cloud computing by bringing computational resources closer to the edge of the network. This paper presents the design and implementation of a oneM2M-compliant fog computing framework tailored for IoT applications. By leveraging the standardized architecture and interoperability features of oneM2M, our proposed framework ensures seamless communication and integration across diverse IoT devices and platforms. We discuss the core components of the architecture, including the fog nodes, data management strategies, and security protocols, which collectively enhance the performance, scalability, and reliability of IoT systems. Additionally, we provide a comprehensive analysis of the framework's effectiveness through real-world case studies and performance evaluations. Our findings demonstrate significant improvements in latency reduction, bandwidth utilization, and overall system responsiveness. This research contributes to the field of IoT by providing a scalable, secure, and efficient fog computing solution, setting the stage for future advancements in smart environments and connected ecosystems.

Fog Computing, Internet of Things (IoT), Edge Computing

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