Year: 2025
Type: preprint
Abstract: 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).
Source: arXiv (Cornell University)
Authors: Sharma, Priyavrat Dev, Sorkhoh, Ibrahim, Maheswaran, Muthucumaru
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6979338707
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