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Article | Open Access

An Efficient Content Caching Strategy for Fog-Enabled Road Side Units in Vehicular Networks

Faareh Ahmed1Babar Mansoor2Muhammad Awais Javed3Abdul Khader Jilani Saudagar4( )
School of Electrical Engineering and Computer Sciences, National University of Sciences and Technology, Islamabad, 44000, Pakistan
Department of Computer Engineering, COMSATS University, Islamabad, 45550, Pakistan
Department of Electrical Engineering, COMSATS University, Islamabad, 45550, Pakistan
Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
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Abstract

Vehicular networks enable seamless connectivity for exchanging emergency and infotainment content. However, retrieving infotainment data from remote servers often introduces high delays, degrading the Quality of Service (QoS). To overcome this, caching frequently requested content at fog-enabled Road Side Units (RSUs) reduces communication latency. Yet, the limited caching capacity of RSUs makes it impractical to store all contents with varying sizes and popularity. This research proposes an efficient content caching algorithm that adapts to dynamic vehicular demands on highways to maximize request satisfaction. The scheme is evaluated against Intelligent Content Caching (ICC) and Random Caching (RC). The obtained results show that our proposed scheme entertains more content-requesting vehicles as compared to ICC and RC, with 33% and 41% more downloaded data in 28% and 35% less amount of time from ICC and RC schemes, respectively.

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Computer Modeling in Engineering & Sciences
Pages 3783-3804

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Cite this article:
Ahmed F, Mansoor B, Javed MA, et al. An Efficient Content Caching Strategy for Fog-Enabled Road Side Units in Vehicular Networks. Computer Modeling in Engineering & Sciences, 2025, 144(3): 3783-3804. https://doi.org/10.32604/cmes.2025.069430

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Received: 23 June 2025
Accepted: 27 August 2025
Published: 30 September 2025
© The Author 2024.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.