Startseite Analyzing key challenges in IOT networks: routing, resource management, and energy efficiency in optical communication using the firefly algorithm
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Analyzing key challenges in IOT networks: routing, resource management, and energy efficiency in optical communication using the firefly algorithm

  • Rajni Rani ORCID logo EMAIL logo und Sharad Sharma ORCID logo
Veröffentlicht/Copyright: 24. April 2025
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

The increasing demand for Internet of Things (IoT) applications necessitates efficient network management in terms of routing, resource allocation, and energy consumption. Optical communication provides a high-speed, reliable medium for IoT connectivity, but optimizing its performance remains a challenge. This research explores the integration of the Firefly Algorithm (FA) for improving routing efficiency, resource management, and energy conservation in optical IoT networks. A comparative analysis with traditional optimization techniques demonstrates the superiority of FA in enhancing network performance. The proposed method is validated through simulation results, showing significant improvements in data transmission latency, energy consumption, and resource utilization. Additionally, this paper integrates insights from recent advancements in nature-inspired routing protocols, machine learning-based optimization techniques, and edge computing solutions.


Corresponding author: Rajni Rani, ECE Department, Maharishi Markandeshwar (Deemed to be University), Mullana (Ambala), India, E-mail:

Acknowledgments

The authors express their sincere gratitude to Maharishi Markandeshwar (Deemed to be University), Mullana, for providing the necessary resources and support to conduct this research.

  1. Research ethics: This research does not involve human or animal participants, and hence ethical approval was not required.

  2. Informed consent: Not applicable. The study did not involve human participants requiring informed consent.

  3. Author contributions: R.R. conceptualized the research, conducted the simulations, and wrote the manuscript. S.S. supervised the research work and contributed to the review and editing of the manuscript. Both authors approved the final version.

  4. Use of Large Language Models, AI and Machine Learning Tools: No content generation or data analysis was performed by AI tools.

  5. Conflict of interest: The authors declare that they have no conflict of interest related to this publication.

  6. Research funding: This research received no specific grant from any funding agency.

  7. Data availability: Data supporting the findings of this study are available from the corresponding author upon reasonable request.

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Received: 2025-03-11
Accepted: 2025-04-05
Published Online: 2025-04-24

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 8.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/joc-2025-0086/pdf
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