Abstract

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.

Highlights

  • At present, the transport protocols of the Open System Interconnection (OSI) model, Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), are facing a lot of challenges in real-time applications over Unmanned Aerial Vehicle (UAV) networks due to specific characteristics such as their time-sensitive nature to the high mobility of nodes

  • The main Quality of Service (QoS) key parameters that should be taken into consideration are packet loss rate and transmission delay [2]

  • For each LB, we simulate the packet loss event starting at different frames in the video sequence within a range of 1000 packets [17], and compute the resulting packet loss rate (PLR)

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Summary

Introduction

The transport protocols of the Open System Interconnection (OSI) model, Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), are facing a lot of challenges in real-time applications over UAV networks due to specific characteristics such as their time-sensitive nature to the high mobility of nodes. In [8], the authors combine cross-layer error protection techniques composed of an error correction code in the link/MAC layer, erasure code in the application layer, and ARQ across the link/MAC layer and application layer While these works show huge potential for multisource download, they are based on simulation results and lack a rigorous analytical model and a good combination of ARQ mechanism and a multi-source download scenario. Since the customization of radio interfaces such as WiFi, 4G, and 5G is often an expensive task, to improve the QoS in a real deployed scenario by developers of UAVs networks, the most acceptable option at minimal cost is to use recovering methods of lost data fragments programmatically on the application layer Such methods with Application Layer ARQ purposes are currently sufficiently studied, but in most cases, scenarios with one transmitter and one receiver are considered.

Multi-Source Streaming Algorithm MS-AL-ARQ
Packet Loss Rate
19. During the prev
Testbed
Topology
Results
MS-AL-ARQ
MS-AL-ARQ Recovery Delay
Average
Packet
10. Average
Quality
6.2.Conclusions
Full Text
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