Enhancing IoT systems through Cloud-Fog-Edge architectures challenges and opportunities

This article examines the deployment and implications of Cloud- Fog-Edge architectures in Internet of Things (IoT) systems, highlighting their significance in enhancing data management and system security across diverse sectors. As IoT ecosystems expand, the necessity for architectures that efficiently handle large volumes of data and ensure real-time processing capabilities becomes paramount. The Cloud-Fog-Edge architecture addresses these needs by distributing computing resources across three layers—cloud, fog, and edge—each optimized for specific tasks within the IoT workflow. We discuss the challenges and solutions associated with interoperability in such multi-layered systems, emphasizing the need for standardized communication protocols and data formats to facilitate seamless interactions between heterogeneous devices and platforms. Furthermore, the article delves into the critical aspects of security within these architectures, outlining strategies for robust data encryption, access management, regular security updates, and comprehensive network activity monitoring to safeguard against unauthorized access and cyber threats. The integration of Cloud-Fog-Edge architectures not only promises enhanced operational efficiency and scalability but also significantly boosts the adaptability of IoT systems to meet evolving technological and operational demands. By providing a detailed analysis of the functionalities, integration challenges, and security practices associated with each architectural layer, this article contributes to a deeper understanding of how Cloud-Fog-Edge frameworks can be optimized to bolster the reliability, efficiency, and security of modern IoT environments.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-25
DOI
https://doi.org/10.1051/e3sconf/202458306012/pdf
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing IoT systems through Cloud-Fog-Edge architectures challenges and opportunities

Springer Link (Chiba Institute of Technology)
IoT and Edge/Fog Computing
article

Enhancing IoT systems through Cloud-Fog-Edge architectures challenges and opportunities

article en

Abstract

This article examines the deployment and implications of Cloud- Fog-Edge architectures in Internet of Things (IoT) systems, highlighting their significance in enhancing data management and system security across diverse sectors. As IoT ecosystems expand, the necessity for architectures that efficiently handle large volumes of data and ensure real-time processing capabilities becomes paramount. The Cloud-Fog-Edge architecture addresses these needs by distributing computing resources across three layers—cloud, fog, and edge—each optimized for specific tasks within the IoT workflow. We discuss the challenges and solutions associated with interoperability in such multi-layered systems, emphasizing the need for standardized communication protocols and data formats to facilitate seamless interactions between heterogeneous devices and platforms. Furthermore, the article delves into the critical aspects of security within these architectures, outlining strategies for robust data encryption, access management, regular security updates, and comprehensive network activity monitoring to safeguard against unauthorized access and cyber threats. The integration of Cloud-Fog-Edge architectures not only promises enhanced operational efficiency and scalability but also significantly boosts the adaptability of IoT systems to meet evolving technological and operational demands. By providing a detailed analysis of the functionalities, integration challenges, and security practices associated with each architectural layer, this article contributes to a deeper understanding of how Cloud-Fog-Edge frameworks can be optimized to bolster the reliability, efficiency, and security of modern IoT environments.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 57%
IoT and Edge/Fog Computing
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