Md. Mahmodul Hasan, Tangina Sultana, Md. Delowar Hossain, Ashis Kumar Mandal, Thien-Thu Ngo, Ga-Won Lee, Eui-Nam Huh,

The journey to cloud as a continuum: Opportunities, challenges, and research directions,

ICT Express,

Volume 11, Issue 4,

2025,

Pages 666-689,

ISSN 2405-9595,

(https://www.sciencedirect.com/science/article/pii/S2405959525000608)

Abstract: The rapid development of the Internet of Things (IoT) has driven a significant shift in computing architectures, leading to the rise of the cloud continuum—a flexible framework that combines cloud services with edge and fog computing. While existing survey papers have contributed valuable insights, they often focus narrowly on specific aspects of the continuum or do not fully address its evolving complexities. These limitations underscore the need for a comprehensive and up-to-date analysis of the field. This study bridges these gaps by presenting an extensive review of the cloud continuum, covering its role in enhancing resource management, improving real-time data processing, integrating machine learning approaches, and optimizing user experiences across diverse applications. We examine how edge devices, fog nodes, and cloud infrastructures synergize to enable decentralized data processing, reducing latency in critical areas such as smart cities, healthcare, and autonomous vehicles. Additionally, this study explores the integration of machine learning across edge, fog, and cloud layers, with a focus on inference and distributed learning methods. By highlighting how these technologies enhance efficiency, scalability, and intelligent decision-making, this review provides a holistic perspective on the cloud continuum. Our analysis offers valuable insights into future research directions, emphasizing innovations that can drive next-generation computing systems toward greater efficiency and adaptability.

Keywords: Distributed computing; Edge computing; Fog computing; IoT; Inference; Machine learning