@article{article_1657823, title={Development of a Greedy Auction-Based Distributed Task Allocation Algorithm for UAV Swarms with Long Range Communication}, journal={ITU Journal of Wireless Communications and Cybersecurity}, volume={2}, pages={37–44}, year={2025}, author={Can, Erdem and Namdar, Mustafa and Başgümüş, Arif}, keywords={Greedy auction-based distributed task allocation algorithm, A2A/A2G communication, LoRa, NB-IoT}, abstract={This study proposes a greedy auction-based distributed task allocation algorithm (GCAA) for swarm unmanned aerial vehicles (UAVs) with long range (LoRa) communication capabilities. Air-to-air (A2A) communication channels are established using LoRa technology to enable inter-agent communication, while air-to-ground (A2G) communication is facilitated through narrowband Internet of Things (NB-IoT) technology. The negotiation phase is conducted over these communication channels. Using LoRa and NB-IoT parameters, a link budget analysis is performed to determine the A2A reference distance, and a k-means clustering algorithm is developed. The proposed algorithm places base stations at cluster centers and prepares a simulation environment. The decentralized algorithm is compared with a greedy optimization algorithm under uninterrupted and interrupted communication scenarios, and the simulation results are presented in MATLAB. The developed distributed task allocation algorithm demonstrates lower system costs and shorter task completion times compared to the conventional greedy optimization algorithm. Additionally, the performance parameters exhibit more excellent stability in cumulative distribution functions.}, number={1}, publisher={İstanbul Technical University}