Machinery & Energetics

This article presents the development and study of a new adaptive routing algorithm for agricultural drones based on the swarm intelligence of a bee colony for self-organizing networks. The proposed approach relies on multi-criteria routing, taking into account throughput, end-to-end delay, node battery level, and network lifetime. The agent model includes packagers, scouts, foragers, and the colony, providing decentralized, multi-path data transmission. Simulation modeling of typical agricultural drone deployment scenarios was conducted, and the algorithm's efficiency was evaluated using packet delivery ratio, throughput, normalized routing load, and routing overhead. Comparative analysis with AODV and OLSR protocols confirmed the superiority of the proposed algorithm, demonstrating its ability to optimally utilize network resources, maintain QoS, and prevent network congestion. The proposed method can be considered a universal solution for routing in modern self-organizing agricultural drone networks.

self-organizing networks, agricultural drones, routing, swarm intelligence, bee colony algorithm