Distributed Caching System in a Decentralized Network of Internet of Things

The Internet of Things (IoT) is evolving rapidly, with countless connected devices generating and exchanging data in real-time. However, managing this data efficiently while considering network constraints, energy consumption, and storage limitations remains a challenge. In this work, we introduce a distributed caching mechanism that allows IoT objects to build co-location relationships and optimize data storage. By clustering objects based on their locations and characteristics, we enable smarter data caching and retrieval, reducing delays and improving network performance. Our approach selects caching nodes based on key factors such as centrality, popularity, energy, and storage capacity, ensuring efficient data handling. The results show that our method significantly improves network lifetime, reduces latency, and enhances overall system efficiency compared to traditional approaches.

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Publication Details

Published
2025-05-15
DOI
https://doi.org/10.1109/iraset64571.2025.11008305
Primary Topic
Caching and Content Delivery
Type
article
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article

Distributed Caching System in a Decentralized Network of Internet of Things

Naoufal El Allali, Mourad Fariss, Abderrahim Zannou, Abdelhak Boulaalam et al.
1 links
Caching and Content Delivery
article

Distributed Caching System in a Decentralized Network of Internet of Things

Naoufal El Allali, Mourad Fariss, Abderrahim Zannou, Abdelhak Boulaalam, Soukaina Bouarourou, El Habib Nfaoui
article en

Abstract

The Internet of Things (IoT) is evolving rapidly, with countless connected devices generating and exchanging data in real-time. However, managing this data efficiently while considering network constraints, energy consumption, and storage limitations remains a challenge. In this work, we introduce a distributed caching mechanism that allows IoT objects to build co-location relationships and optimize data storage. By clustering objects based on their locations and characteristics, we enable smarter data caching and retrieval, reducing delays and improving network performance. Our approach selects caching nodes based on key factors such as centrality, popularity, energy, and storage capacity, ensuring efficient data handling. The results show that our method significantly improves network lifetime, reduces latency, and enhances overall system efficiency compared to traditional approaches.

Abdelmalek Essaâdi University (MA), Mohamed I University (MA), Sidi Mohamed Ben Abdellah University (MA)
Openalex Percentile: Top 88%
Caching and Content Delivery
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Distributed Caching System in a Decentralized Network of Internet of Things — Naoufal El Allali, Mourad Fariss, et al. · (2025) | TGRS Research Map | TGRS