A Study on the Survival Enhancement Strategy of Drone Ad-Hoc Network

• Chungman Oh,
• Seokjoong Kang,

Vol. 19, No. 12, December 31, 2025
10.3837/tiis.2025.12.008, Download Paper (Free):

• Artificial Intelligence(AI)
• System Architecture
• ad-hoc network
• Network survivability

Abstract

This study proposes and validates innovative strategies to address the challenge of network survivability in Ad-hoc drone systems exposed to electronic warfare threats such as jamming attacks. Specifically, it integrates the drone’s Dynamic Environmental Awareness and Autonomous Flight Path Planning capabilities to enhance survivability through improved sustainability and resilience. The evaluation was conducted in a simulation environment under three scenarios—baseline (pre-attack), during attack, and post-attack—using Connectivity Ratio (CR), Packet Delivery Ratio (PDR), and Average Delay as the core performance metrics. The simulation results show that network performance deteriorated sharply at the onset of jamming. In particular, the PDR dropped by up to 35.37% compared to the baseline, while the average delay increased by 62.02%, indicating a severe impact on communication reliability. However, the proposed strategy enabled the drone network to demonstrate outstanding recovery and sustainability. After the termination of the attack, the network rapidly recovered: the average CR increased by 33.33% compared to its minimum value during the attack (0.60), and the PDR improved by 43.40% compared to its lowest point (0.53). More notably, the post-attack performance even exceeded the baseline: the average CR rose by 10.65% above the pre-attack baseline, while the average delay decreased by 18.29%, reflecting enhanced efficiency. In conclusion, this study provides quantitative evidence that autonomous drone maneuvering and dynamic network reconfiguration can significantly reinforce the robustness, resilience, and sustainability of Ad-hoc drone networks, even under adversarial conditions such as jamming attacks.

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