Beyond Markovian queue: a heuristic optimization of a fluid queue with a delay-aware retrial strategy for unprecedented energy efficiency in 5G-based ad hoc networks

An energy crisis poses a significant challenge in wireless communication networks and looms large due to power-constrained supply and unforeseeable data traffic. As a solution, optimizing energy usage is crucial for enhancing data transmission efficiency and alleviating data overload. Additionally, addressing delays is vital for maintaining energy stability. Our model is dedicated to optimizing energy levels to significantly prolong the system's performance during data transmission. The proposed work thoroughly analyzes the impact of implementing a delay-aware mechanism using a fluid retrial queueing model to enhance energy optimization. Moreover, pioneered a heuristic approach for fluid queueing analysis to effectively reduce energy usage. Our numerical visualizations validate the analytical results, demonstrating an impressive 83.7% accuracy compared to traditional queueing methods.

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Publication Details

Journal
Systems Science & Control Engineering
Published
2024-11-19
DOI
https://doi.org/10.1080/21642583.2024.2427027
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
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article

Beyond Markovian queue: a heuristic optimization of a fluid queue with a delay-aware retrial strategy for unprecedented energy efficiency in 5G-based ad hoc networks

K. Nandhini, V Vidhya
Systems Science & Control Engineering
Advanced MIMO Systems Optimization
article

Beyond Markovian queue: a heuristic optimization of a fluid queue with a delay-aware retrial strategy for unprecedented energy efficiency in 5G-based ad hoc networks

K. Nandhini, V Vidhya
article en

Abstract

An energy crisis poses a significant challenge in wireless communication networks and looms large due to power-constrained supply and unforeseeable data traffic. As a solution, optimizing energy usage is crucial for enhancing data transmission efficiency and alleviating data overload. Additionally, addressing delays is vital for maintaining energy stability. Our model is dedicated to optimizing energy levels to significantly prolong the system's performance during data transmission. The proposed work thoroughly analyzes the impact of implementing a delay-aware mechanism using a fluid retrial queueing model to enhance energy optimization. Moreover, pioneered a heuristic approach for fluid queueing analysis to effectively reduce energy usage. Our numerical visualizations validate the analytical results, demonstrating an impressive 83.7% accuracy compared to traditional queueing methods.

Systems Science & Control EngineeringVol. 12(1)
Vellore Institute of Technology University (IN)
Affordable and clean energy
Openalex Percentile: Top 82%
Advanced MIMO Systems Optimization
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