Advances in the Internet of Things are revolutionizing data acquisition, enhancing artificial intelligence and quality of service. Unmanned Aerial Vehicles (UAVs) provide an efficient data-gathering solution across varied environments. This paper addresses challenges in integrating UAVs for large scale data operations, including mobility, multi-hop paths, and optimized multi-source information transfer. We propose a collaborative UAV framework that enables efficient data sharing with minimal communication overhead, featuring adaptive power control and dynamic resource allocation. Formulated as an NP-hard Integer Linear Program, our approach uses heuristic algorithms to optimize routing through UAV hubs. Simulations show promise in terms of computation time (99% speedup) and outcome (down to 14% deviation from the optimal).
@article{arxiv.2504.08403,
title = {Optimizing Collaborative UAV Networks for Data Efficiency in IoT Ecosystems},
author = {Priyavrat Dev Sharma and Ibrahim Sorkhoh and Muthucumaru Maheswaran},
journal= {arXiv preprint arXiv:2504.08403},
year = {2025}
}
Comments
7 pages, 6 figures. Accepted for presentation at the IEEE ICC Workshop 2025 in Montreal, Canada