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<p>Internet of Things (IoT), fog computing, and cloud services are revolutionary technologies. These technologies enable efficient collection, processing, and management of data. Today, as the importance of data is growing, the proliferation of IoT devices has accelerated. Fog computing acts as a decentralized intermediary and facilitates real-time data processing. And cloud services provide robust storage and scalable computing capabilities. However, data management, especially large-scale data, poses a significant challenge in the integration of IoT, fog computing, and cloud services. It requires efficient management of the vast amount of real-time data generated by IoT devices while ensuring seamless interoperability and scalability across decentralized and centralized systems. Given the importance of integrating IoT, fog, and cloud technologies for efficient data management, we present a systematic literature review (SLR) of 127 research articles and 17 review articles published up to 2025 that focus on key areas of these technologies. We propose two classifications; one addressing data management strategies and the other exploring real-world applications. We also review and discuss real-world applications, common evaluation environments, programming languages, simulators, and evaluation criteria in IoT, fog computing, and cloud services in recent papers. In addition, we identify common challenges, future directions, open issues, and a roadmap for researchers.</p>

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Toward a unified computing paradigm: a survey and roadmap for data management in integrated IoT, fog, and cloud services

  • 期刊论文

  • 发表日期：

    2026年2月28日

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  • Atefeh Hemmati,
  • Navid Khaledian,
  • Amir Masoud Rahmani

摘要

Internet of Things (IoT), fog computing, and cloud services are revolutionary technologies. These technologies enable efficient collection, processing, and management of data. Today, as the importance of data is growing, the proliferation of IoT devices has accelerated. Fog computing acts as a decentralized intermediary and facilitates real-time data processing. And cloud services provide robust storage and scalable computing capabilities. However, data management, especially large-scale data, poses a significant challenge in the integration of IoT, fog computing, and cloud services. It requires efficient management of the vast amount of real-time data generated by IoT devices while ensuring seamless interoperability and scalability across decentralized and centralized systems. Given the importance of integrating IoT, fog, and cloud technologies for efficient data management, we present a systematic literature review (SLR) of 127 research articles and 17 review articles published up to 2025 that focus on key areas of these technologies. We propose two classifications; one addressing data management strategies and the other exploring real-world applications. We also review and discuss real-world applications, common evaluation environments, programming languages, simulators, and evaluation criteria in IoT, fog computing, and cloud services in recent papers. In addition, we identify common challenges, future directions, open issues, and a roadmap for researchers.