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Titre: Data Caching in Edge Computing: A Survey
Auteur(s): Kara, Meliha Çağla
Benlakehal, Mohamed Elamine
Shayea, Ibraheem
Tussupov, Akhmet
Rzayeva, Leila
Mots-clés: Data Caching
Edge Computing
Edge-Cloud Synergy
IoT
Mobile Crowdsensing
Optimization
Date de publication: 2024
Editeur: Institute of Electrical and Electronics Engineers Inc.
Collection/Numéro: 2024 IEEE 4th International Conference on Smart Information Systems and Technologies (SIST), Astana, Kazakhstan, 2024;pp. 433-439
Résumé: As the Internet of Things (IoT) generates ever-increasing data streams, traditional cloud-centric architectures face crippling challenges in network latency, bandwidth consumption, and resource constraints. This paper explores how data caching in edge computing environments emerges as a potent solution, significantly impacting latency reduction, network efficiency, and overall system performance. We comprehensively review the landscape of edge IoT and data caching, analyze caching benefits and complexities, and delve into architectural integration, caching strategies, and algorithms tailored to address specific IoT challenges. Through case studies in chosen application domains, we quantify the performance improvements enabled by effective caching and pave the way for future research exploring novel caching methodologies and optimization techniques in the dynamic world of edge IoT.
URI/URL: https://ieeexplore.ieee.org/document/10629324
10.1109/SIST61555.2024.10629324
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/14341
ISBN: 979-835037486-5
Collection(s) :Communications Internationales

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