Drones are frequently used for the delivery of materials or other goods, and to facilitate the capture and transmission of data. Moreover, drone networks have gained significant interest in a number of scenarios, such as in quarantined or isolated areas, following technical damage due to a disaster, or in non-urbanized areas without communication infrastructure. In this context, we propose a network of drones that are able to fly on a map covered by regular polygons, with a well-established mobility schedule, to carry and transfer data. Two means exist to equidistantly cover an area with points, namely, grouping the points into equilateral triangles or squares. In this study, a network of drones that fly in an aerial area divided into squares was proposed and investigated. This network was compared with the case in which the area is divided into equilateral triangles. The cost of the square drone network was lower than that of the triangular network with the same cell length, but the efficiency factors were better for the latter. Two situations related to increasing the drone autonomy using drone charging or battery changing stations were analyzed. This study proposed a Delay Tolerant Network (DTN) to optimize the transmission of data. Multiple simulation studies based on experimental flight tests were performed using the proposed algorithm versus five traditional DTN methods. A light Wi-Fi Arduino development board was used for the data transfer between drones and stations using delivery protocols. The efficiency of data transmission using single-copy and multiple-copy algorithms was analyzed. Simulation results showed a better performance of the proposed Time-Dependent Drone (TD-Drone) Dijkstra algorithm compared with the Epidemic, Spray and Wait, PRoPHET, MaxProp, and MaxDelivery routing protocols.
Keywords: DTN; data delivery; drones; mobility schedule; network; routing algorithms.