Intelligent Hello Dissemination Model for FANET Routing Protocols

The routing mechanisms in flying ad-hoc networks (FANETs) using unmanned aerial vehicles (UAVs) have been a challenging issue for many reasons, such as its high speed and different directions of use. In FANETs, the protocols send hello messages periodically maintenance routes. However, that are sent network increase bandwidth wastage on some occasions excessive number can also cause problem energy loss. Scarce works deal with dynamic UAVs scenarios, treat several other problems, simultaneously. Generally, existing solutions configure interval to an long or short time period originating delay neighbors discovery. Thus, self-acting approach is necessary calculating exact aim reduce loss; this needs be low complex terms computational resource consumption. order solve problem, intelligent Hello dissemination model, AI-Hello, based reinforcement learning algorithms, adapts message scheme proposed produce dense reward structure, facilitating learning. Experimental results, considering FANET scenarios range 40 UAVs, show method implemented two widely adopted (AODV OLSR) saved 30.86% 27.57% consumption comparison original AODV OLSR protocols, respectively. Furthermore, our proposal reached better performance results relation state-of-the-art methods same parameters, overhead, packet delivery ratio, throughput delay.