Evaluation of Flying Ad Hoc Network Topologies, Mobility Models, and IEEE Standards for Different Video Applications

Nowadays, drones became very popular with the enhancement of the technological progress of moving devices with a connection to each other, known as Flying Ad Hoc Network (FANET). It is used in most worldwide necessary life scenarios such as video recording, search and rescue, military missions, moving items between different areas, and many more. This leads to the necessity to evaluate different network strategies between these flying drones, which are essential to improve their quality of performance in the field. Several challenges must be addressed to effectively use FANET, to provide stable and reliable transmission for different types of data during vast changing topologies, such as different video sizes, different types of mobility models, recent Wireless Fidelity standards, types of routing protocols used, security problems, and many more. In this paper, a fully comprehensive analysis of FANET will be done to evaluate and enhance these challenges that concern different video types, mobility models, and IEEE 802.11n standards for best performance, by measuring throughput, retransmission attempt, and delay metrics. The result shows that Gauss–Markov mobility model gives the highest result using Ad Hoc On-Demand Vector and lowest delay, whereas for retransmission attempts, 2.4 GHz frequency has the lowest as it can reach more coverage area than 5 GHz

FANET Drone’s 4K Data Applications, Mobility Models and Wi-Fi IEEE802.11n Standards, Journal of Telecommunications and Information Technology, 2021, nr 1

With growing popularity of unmanned aerial vehicles (UAVs), the importance of flying ad-hoc networks (FANETs) is enhanced by such applications as 4K video recording, communications in search and rescue missions and goods deliveries, to name just a few. This, in turn, stimulates research on different topologies of networks existing between UAVs, with studies in this field being essential to improving performance of such networks. Several problems must be solved to effectively use UAVs in order to offer stable and reliable massive data transmission capabilities, taking into consideration quickly changing FANET topologies, types of routing, security issues, etc. In this paper, a comprehensive evaluation of FANETs used by UAVs is presented in terms of communication network challenges, data types, mobility models and standards applied in order to achieve best performance. The evaluation presented herein covers such areas as data throughput, retransmission attempts and delay

A Course-Aware Opportunistic Routing Protocol for FANETs

In recent years, unmanned aerial vehicles (UAVs) have gained popularity in various applications and services in both the military and civilian domains. Compared with the single-UAV scenario, flying ad hoc networks (FANETs) consisting of ground stations (GSs) and UAVs have the advantages of flexible configuration and wide coverage. However, due to significant mobility and highly dynamic topology, designing reliable and efficient routing protocols for FANETs is a challenging task. In this paper, we consider a network that comprises multiple flying UAVs and GSs to transfer messages by multi-hop relaying. We propose a routing protocol, named course-aware opportunistic routing for FANETs (CORF). The UAVs cooperatively exchange aeronautical data with others. The source UAV node (SUN) calculates the transfer probabilities to different neighbors by jointly considering the positions of its neighbors and the destination node. Based on the direction information and the transfer probabilities, the SUN selects the next-hop relay nodes among the neighbor UAVs and GSs. This process continues until the destination node receives the message. The simulation results demonstrate that, the proposed CORF protocol achieves significant performance superiority as compared with the traditional protocols in terms of message delivery rate and network latency. - 2013 IEEE.This work was supported in part by the National Natural Science Foundation of China under Grant 61571370, Grant 61601365, Grant 61901381, Grant 61801388, Grant 61901378, and Grant 61901379, in part by the Science and Technology Research Program of Shaanxi Province under Grant 2018ZDCXL-GY-03-04, Grant 2019ZDLGY07-10, Grant 2019JQ-253, Grant 2019JQ-631, and Grant 2019JM-345, in part by the Advance Research Program on Common Information System Technologies under Grant 315075702, in part by the Postdoctoral Science Foundation of China under Grant BX20180262, Grant BX20190287, Grant 2018M641020, and Grant 2018M641019, and in part by the Fundamental Research Funds for the Central Universities under Grant G2019KY05302, Grant 31020180QD095, and Grant 3102017OQD091.Scopu