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