Optimizing energy consumption in passive optical networks through renewable integration
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Sweta Bhardwaj
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Mukesh Ruhela
Abstract
Passive optical networks (PONs) are widely recognized for their high bandwidth, scalability, and cost-effectiveness in modern broadband access systems. However, the increasing global demand for high-speed data services has led to concerns over the energy consumption and environmental impact of large-scale PON deployments. This study investigates the integration of renewable energy sources – such as solar and wind power – into PON architectures to optimize energy usage and reduce carbon emissions. A hybrid power supply model is proposed, wherein renewable energy generation is complemented by smart energy management techniques to ensure reliable operation under variable supply conditions. The research evaluates the performance of the proposed approach through simulation and analytical modeling, focusing on parameters such as power consumption, network uptime, and greenhouse gas (GHG) reduction potential. Results demonstrate that renewable-integrated PONs can achieve up to XX% reduction in grid energy consumption while maintaining quality of service (QoS) standards. This work highlights the potential of combining optical access technologies with sustainable energy solutions to enable greener, more energy-efficient communication networks.
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Research ethics: DR. VIKAS SHARMA and DR. PRITIBHA SUKHROOP declare that this research was conducted in compliance with ethical.
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Informed consent: Informed consent was obtained from all participants, and data collected were anonymized to protect confidentiality.
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Author contributions: This manuscript is original, has not been published elsewhere, and all contributions have been appropriately cited. All procedures were conducted in accordance with relevant guidelines.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors confirm that there are no conflicts of interest, and any financial support received for this study has been disclosed.
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Research funding: None declared.
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Data availability: Data supporting this study’s findings are available from the corresponding author upon reasonable request, and the research complies with the general data protection regulation (GDPR) where applicable.
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