A Novel Deep Energy Efficient Hello Packet Scheduling for Ad Hoc Networks in Unmanned Aerial Vehicles

Hemant Kumar Saini1,Email

Kusumlata Jain2

1Department of Computer Science and Engineering, Manipal University Jaipur, Dehmi Kalan, Jaipur 303007, Rajasthan, India.
2Department of Computer and Communication Engineering, Manipal University Jaipur, Dehmi Kalan, Jaipur 303007, Rajasthan, India.

Abstract

From the previous pandemic stage, the world is emerging with a demand for wireless communications for the various essential mission-related data collection, dissemination, and deliveries in the areas where humans can’t reach. One of the most notable innovations in the field of aircraft vehicles is the formation of an aerial ad hoc network (AANET) by a group of aircraft vehicles communicating collectively in an ad hoc fashion. AANET has been widely explored in various critical missions, but due to their high mobility characteristic, they anticipated challenges like packet loss, energy drain, and link breakages. Since AANET fuels in the air are battery-driven, the flight speed exponentially decreases due to sudden drifting, etc., which affects network performance, energy consumption, and flight time. This paper reveals the limitations in the era of AANET and designs a novel deep energy efficient hello packet scheduling strategy using a deep learning strategy with the NS3. This would extend the lifetime of the UAV flight by saving energy and enhance the performance metrics that are required. This proposed research may help to better understand the temporal and spatial characteristics of the AANET in 3D targeted scenarios and sustain significant network performance metrics like packet delivery, throughputs, end-to-end delay, energy consumption, etc.

A Novel Deep Energy Efficient Hello Packet Scheduling for Ad Hoc Networks in Unmanned Aerial Vehicles