Application Layer ARQ Algorithm for Real-Time Multi-Source Data Streaming in UAV Networks

• Main Authors: Mohammed Amin Lamri, Albert Abilov, Danil Vasiliev, Irina Kaisina, Anatoli Nistyuk
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Sensors
• Subjects: buffer management; UAVs; real-time application; delay; packet loss rate; jitter
• Online Access: https://www.mdpi.com/1424-8220/21/17/5763

Because of the specific characteristics of Unmanned Aerial Vehicle (UAV) networks and real-time applications, the trade-off between delay and reliability imposes problems for streaming video. Buffer management and drop packets policies play a critical role in the final quality of the video received by the end station. In this paper, we present a reactive buffer management algorithm, called Multi-Source Application Layer Automatic Repeat Request (MS-AL-ARQ), for a real-time non-interactive video streaming system installed on a standalone UAV network. This algorithm implements a selective-repeat ARQ model for a multi-source download scenario using a shared buffer for packet reordering, packet recovery, and measurement of Quality of Service (QoS) metrics (packet loss rate, delay and, delay jitter). The proposed algorithm MS-AL-ARQ will be injected on the application layer to alleviate packet loss due to wireless interference and collision while the destination node (base station) receives video data in real-time from different transmitters at the same time. Moreover, it will identify and detect packet loss events for each data flow and send Negative-Acknowledgments (NACKs) if packets were lost. Additionally, the one-way packet delay, jitter, and packet loss ratio will be calculated for each data flow to investigate the performances of the algorithm for different numbers of nodes under different network conditions. We show that the presented algorithm improves the QoS of the video data received under the worst network connection conditions. Furthermore, some congestion issues during deep analyses of the algorithm’s performances have been identified and explained.