Green, scalable and efficient IoT architecture

In many applications, the Internet of Things (IoT) has revolutionized data collection, processing, and utilization. However, IoT faces challenges in energy consumption and latency, as devices often send data to distant servers, which is energyintensive and causes delays. Fog computing addresses this by enabling data processing closer to IoT devices. Despite its benefits, fog computing deployment, especially placing fog nodes near devices, requires substantial investments and complex implementation processes, hindering widespread adoption. Participatory computing solutions have been proposed to enhance fog architectures by leveraging underutilized network resources. However, they often fail to efficiently manage the fog infrastructure, leading to the need for numerous fog nodes near connected objects and creating bottlenecks despite available participatory resources. To resolve these issues, we propose a participatory fog computing architecture that optimizes the use of underutilized resources like smartphones, laptops, and desktop computers around IoT devices. This reduces latency and energy consumption while maximizing network efficiency. Our approach promotes sustainable and efficient IoT and fog infrastructure management by decreasing transmission load and energy consumption. Simulations show that our architecture enables more efficient resource utilization, providing a viable solution to IoT node deployment challenges. It reduces costs and simplifies implementation while ensuring optimal performance under varying conditions.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/fmec62297.2024.10710309
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35
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article

Green, scalable and efficient IoT architecture

Ahmed Lounis, Abdelmadjid Bouabdallah, Safa Bendaouia
1 citations
IoT and Edge/Fog Computing
0.35
article

Green, scalable and efficient IoT architecture

Ahmed Lounis, Abdelmadjid Bouabdallah, Safa Bendaouia
article en
1 citations

Abstract

In many applications, the Internet of Things (IoT) has revolutionized data collection, processing, and utilization. However, IoT faces challenges in energy consumption and latency, as devices often send data to distant servers, which is energyintensive and causes delays. Fog computing addresses this by enabling data processing closer to IoT devices. Despite its benefits, fog computing deployment, especially placing fog nodes near devices, requires substantial investments and complex implementation processes, hindering widespread adoption. Participatory computing solutions have been proposed to enhance fog architectures by leveraging underutilized network resources. However, they often fail to efficiently manage the fog infrastructure, leading to the need for numerous fog nodes near connected objects and creating bottlenecks despite available participatory resources. To resolve these issues, we propose a participatory fog computing architecture that optimizes the use of underutilized resources like smartphones, laptops, and desktop computers around IoT devices. This reduces latency and energy consumption while maximizing network efficiency. Our approach promotes sustainable and efficient IoT and fog infrastructure management by decreasing transmission load and energy consumption. Simulations show that our architecture enables more efficient resource utilization, providing a viable solution to IoT node deployment challenges. It reduces costs and simplifies implementation while ensuring optimal performance under varying conditions.

Université de Technologie de Compiègne (FR), Centre National de la Recherche Scientifique (FR), Sorbonne Université (FR), Heuristics and Diagnostics for Complex Systems (FR)
Openalex Percentile: Top 38%
IoT and Edge/Fog Computing
0.35
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