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The next generation wireless networks need efficient mechanisms for datadissemination that should support users with better Quality of Service (QoS).Nevertheless, the existing solutions are unable to handle this demand andrequire either network redeployment or replanning. Moreover, this upsurges theoverall operational cost and complexity of the network. This problem can beaddressed by deploying Unmanned Aerial Vehicles (UAVs), which can act ason-demand relays in next generation wireless networks. In this work, a novelstrategy comprising a series of algorithms based on neural networks is devised,which resolves the issues related to data dissemination, QoS, capacity, andcoverage. When compared with the existing methods, the proposed approachdemonstrates better outcomes for various parameters, namely, throughput,message disseminations, service dissemination rate, UAV allocation time, routeacquisition delay, link utilization and signal to noise ratio for end users.The experimental results exhibit the fact that the proposed approach utilizes39.6%, 41.6%, 43.5%, 44.4%, and 46.9% lesser iterations than the EEDD, A-Star,OCD, GPCR, and GyTAR, respectively. Therefore, it is evident that the proposedapproach surpasses the existing methods by means of superior performance andaugmented efficiency.

QoS-Aware Routing in Wireless Networks Using Aerial Vehicles