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<p>The Delay-Tolerant Network (DTN) routing was introduced to solve data dissemination issues under sparse Flying Ad Hoc Networks (FANETs) to face the circumstances of intermittent connectivity under inter-Unmanned Aerial Vehicle (UAV) communication, respectively. Meanwhile, ensuring the delay-tolerant information forwarding in 3D brings additional complications compared to ground vehicular communication, notably the quick UAV speed and unstable UAV energy resources, entailing short UAV-to-UAV (U2U) connection time, besides the impact of weather disturbances on UAV mobility. Conventional Flying Delay-Tolerant Networks (FDTN) routing solutions tried to solve those issues by referring to the geographic location of UAVs and probabilistic DTN routing methods to support the relay Store-Carry-and-Forward (SCF) UAV selection decision. The latter produced convincing Quality of Service (QoS) performances in small areas for specialized applications. However, the conventional FDTN routing cannot keep the same performance under large 3D areas. Therefore, this paper introduces nature-inspired computation to extend the geographic applicability of U2U-supported applications, covering multiple services under rural and urban zones. For this purpose, two nature-inspired metaheuristics are implemented: The Glowworm Swarm Optimization (GSO) and Intelligent Water-Drop (IWD) algorithms. GSO is exploited to explore relay UAVs for distant local zones, while IWD manages the SCF of data bundles following predefined map-based transportation trajectories. This approach seeks to reduce the number of dropped data bundles sent to distant data requesters. The simulation tests on a large mobility area indicate that the proposed solution tallies optimal delivery probability rates and stable data forwarding delays compared to a few state-of-the-art FDTN routing schemes.</p>

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Improved data forwarding strategy for Flying Delay-Tolerant Networks (FDTNs) using a hybrid nature-inspired optimization approach

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  • 出版模式：

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  • 发表日期：

    2026年6月3日

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  • Youcef Azzoug

摘要

The Delay-Tolerant Network (DTN) routing was introduced to solve data dissemination issues under sparse Flying Ad Hoc Networks (FANETs) to face the circumstances of intermittent connectivity under inter-Unmanned Aerial Vehicle (UAV) communication, respectively. Meanwhile, ensuring the delay-tolerant information forwarding in 3D brings additional complications compared to ground vehicular communication, notably the quick UAV speed and unstable UAV energy resources, entailing short UAV-to-UAV (U2U) connection time, besides the impact of weather disturbances on UAV mobility. Conventional Flying Delay-Tolerant Networks (FDTN) routing solutions tried to solve those issues by referring to the geographic location of UAVs and probabilistic DTN routing methods to support the relay Store-Carry-and-Forward (SCF) UAV selection decision. The latter produced convincing Quality of Service (QoS) performances in small areas for specialized applications. However, the conventional FDTN routing cannot keep the same performance under large 3D areas. Therefore, this paper introduces nature-inspired computation to extend the geographic applicability of U2U-supported applications, covering multiple services under rural and urban zones. For this purpose, two nature-inspired metaheuristics are implemented: The Glowworm Swarm Optimization (GSO) and Intelligent Water-Drop (IWD) algorithms. GSO is exploited to explore relay UAVs for distant local zones, while IWD manages the SCF of data bundles following predefined map-based transportation trajectories. This approach seeks to reduce the number of dropped data bundles sent to distant data requesters. The simulation tests on a large mobility area indicate that the proposed solution tallies optimal delivery probability rates and stable data forwarding delays compared to a few state-of-the-art FDTN routing schemes.