An enhanced AHP-TOPSIS-based clustering algorithm for high-quality live video streaming in flying ad hoc networks

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.