ORIGINAL RESEARCH article
Front. Commun. Netw.
Sec. IoT and Sensor Networks
This article is part of the Research TopicNon-Terrestrial IoT Networks: Architectures, Applications, and Future ChallengesView all articles
Adaptive Ant Colony Methods for UAV LEO Coordination in Non Terrestrial IoT
Provisionally accepted
- KIIT University, Bhubaneswar, India
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In this work, an adaptive CO framework is proposed for dynamic task coordination in heterogeneous NTN-IoT systems that combine UAVs and LEO satellites. The framework handles stochastic mobility, intermittent connectivity, and latency-limited tasks through adaptive pheromone learning, heuristic control, and multi-timescale scheduling. It assumes a hierarchical co-optimization between edge-side task assignment on UAV swarms and relay scheduling over LEO passes. Robustness to system dynamics is ensured by event-triggered pheromone resets and distributionally robust cost design. Comparisons with classical ACO and recent meta-heuristics show higher task completion ratio, lower end-to-end latency, and improved energy-normalized throughput under varying orbital geometries, traffic changes, and link failures. The results highlight the potential of this approach for resilient NTN-IoT operations in disaster response, precision agriculture, and maritime monitoring.
Keywords: Non-terrestrial IoT, UAV swarms, LEO satellites, adaptive colony optimization, Dynamic task allocation, Scheduling, Edge computing, connectivity-aware orchestration
Received: 23 Aug 2025; Accepted: 06 Oct 2025.
Copyright: © 2025 Mohapatra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Hitesh Mohapatra, hiteshmahapatra@gmail.com
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