[HTML][HTML] Cache in fog computing design, concepts, contributions, and security issues in machine learning prospective

MA Naeem, YB Zikria, R Ali, U Tariq, Y Meng… - Digital Communications …, 2023 - Elsevier
MA Naeem, YB Zikria, R Ali, U Tariq, Y Meng, AK Bashir
Digital Communications and Networks, 2023Elsevier
The massive growth of diversified smart devices and continuous data generation poses a
challenge to communication architectures. To deal with this problem, communication
networks consider fog computing as one of promising technologies that can improve overall
communication performance. It brings on-demand services proximate to the end devices
and delivers the requested data in a short time. Fog computing faces several issues such as
latency, bandwidth, and link utilization due to limited resources and the high processing …
Abstract
The massive growth of diversified smart devices and continuous data generation poses a challenge to communication architectures. To deal with this problem, communication networks consider fog computing as one of promising technologies that can improve overall communication performance. It brings on-demand services proximate to the end devices and delivers the requested data in a short time. Fog computing faces several issues such as latency, bandwidth, and link utilization due to limited resources and the high processing demands of end devices. To this end, fog caching plays an imperative role in addressing data dissemination issues. This study provides a comprehensive discussion of fog computing, Internet of Things (IoTs) and the critical issues related to data security and dissemination in fog computing. Moreover, we determine the fog-based caching schemes and contribute to deal with the existing issues of fog computing. Besides, this paper presents a number of caching schemes with their contributions, benefits, and challenges to overcome the problems and limitations of fog computing. We also identify machine learning-based approaches for cache security and management in fog computing, as well as several prospective future research directions in caching, fog computing, and machine learning.
Elsevier
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