Routing Protocols in FANETs with Future Enhancements

Year : 2025 | Volume : 15 | Issue : 03 | Page : 8 13
    By

    Prachi Dev,

  • Neeta Singh,

  1. Student, School of Information and Communication Technology Gautam Buddha University Greater Noida, Uttar Pradesh, India
  2. Assistant Professor, School of Information and Communication Technology, Gautam Buddha University Greater Noida, Uttar Pradesh, India

Abstract

Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology changes, heavily challenges conventional routing protocols. Traditional mechanisms such as AODV, DSDV, and OLSR are unable to handle such scenarios due to their centralized or fixed nature. The latest intelligent methods, such as Q-learning-based Smart Clustering Routing (QSCR) and Deep Evolutionary Multi-Agent Deep Deterministic Policy Gradient (DE-MADDPG), have enhanced scalability and energy efficiency. However, they continue to lag in terms of convergence delays and adaptability in high-density or topologically heterogeneous environments. This study presents an intelligent routing architecture blending Federated Learning (FL), Graph Neural Networks (GNNs), Hierarchical Reinforcement Learning (HRL), and Reconfigurable Intelligent Surfaces (RIS) to build a scalable, energy-efficient, and adaptive FANET setting. Our combined approach utilizes decentralized training to maintain privacy and minimize communication overhead, an RIS protocol to enhance link quality, and HRL-aided clustering for efficient decision-making. Simulation and comparative analysis with baseline protocols validate the performance of this model against important metrics like packet delivery ratio, routing overhead, and energy consumption. This research contributes to the state-of-the-art of FANET routing by integrating several AI-based and communication-boosting technologies into one, providing a forward-compatible template for the UAV network design of a next-generation aerial system.

Keywords: FANETs, UAVs, AODV, DSDV, OLSR, QSCR, DE-MADDPG, RIS, GNN, HRL

[This article belongs to Journal of Aerospace Engineering & Technology ]

How to cite this article:
Prachi Dev, Neeta Singh. Routing Protocols in FANETs with Future Enhancements. Journal of Aerospace Engineering & Technology. 2025; 15(03):8-13.
How to cite this URL:
Prachi Dev, Neeta Singh. Routing Protocols in FANETs with Future Enhancements. Journal of Aerospace Engineering & Technology. 2025; 15(03):8-13. Available from: https://journals.stmjournals.com/joaet/article=2025/view=228098


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Regular Issue Subscription Review Article
Volume 15
Issue 03
Received 11/07/2025
Accepted 25/08/2025
Published 25/09/2025
Publication Time 76 Days
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