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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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