Flying ad hoc networks (FANETs) consist of unmanned aerial vehicles (UAVs) with energy limitations which have the capability of sending recorded live video stream to supervise their surroundings completely and intelligently. Although significant efforts have been made by previous researchers to increase the quality of received video stream as a main mission of a UAV, challenges like energy consumption, effective use of bandwidth, effective clustering among UAVs and their intelligent communication with ground stations especially at the same time have not been noticed in the past research studies simultaneously. Therefore, in the proposed method, for the first time, a low complex AHP-TOPSIS hybrid algorithm has been used for effective clustering in FANETs. Cluster heads (CHs), in addition to imaging, receive the recorded videos frames by other UAVs through Wi-Fi and send them to the ground station through 5G connection. Using AHP-TOPSIS algorithm, the ground controller intelligently specifies which UAVs should be CH in regular intervals. Therefore, because of UAVs’ swarm reduction and, at the same time, effective use of bandwidth, traffic and delay in transferring live video frames are reduced which leads to achieving high video quality in ground station and, at the same time, reduction UAV energy consumption. The results of numerous simulations in OMNET + + under different conditions show that the parameters of video quality percentage, UAV average energy consumption and the number of necessary cluster head have been significantly improved when two famous mobility models including Paparazzi and Random Waypoint are considered comparing other methods.

飞行自组织网络（FANET）由能量受限的无人飞行器（UAV）组成，它们能够发送录制的实时视频流，以完全智能地监视周围环境。尽管以前的研究人员已经做出了巨大的努力来提高接收视频流的质量，这是无人机的主要任务，但是挑战仍然存在，例如能耗，有效利用带宽，无人机之间的有效群集以及它们与地面站的智能通信等。过去的研究没有同时注意到时间。因此，在提出的方法中，首次将低复杂度的AHP-TOPSIS混合算法用于FANET中的有效聚类。除成像外，簇头（CH）通过Wi-Fi接收其他无人机记录的视频帧，并通过5G连接将其发送到地面站。地面控制器使用AHP-TOPSIS算法，智能地指定应定期间隔将哪些无人机作为CH。因此，由于减少了无人机的数量，同时有效地利用了带宽，减少了传输实况视频帧的流量和延迟，这导致在地面站获得高质量的视频，同时减少了无人机的能量消耗。在不同条件下在OMNET ++中进行的大量仿真结果表明，视频质量百分比的参数，