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

Mohammed Amin Lamri1, Albert Abilov1, Danil Vasiliev1

  • 1Department of Networks and Telecommunication Systems, Faculty of Instrumental Engineering, Kalashnikov Izhevsk State Technical University, ul. Studencheskaya, 7, 426069 Izhevsk, Russia.

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Summary
This summary is machine-generated.

A new Multi-Source Application Layer Automatic Repeat Request (MS-AL-ARQ) algorithm improves real-time video streaming quality over Unmanned Aerial Vehicle (UAV) networks. It enhances Quality of Service (QoS) by managing buffers and retransmissions, even in poor network conditions.

Keywords:
UAVsbuffer managementdelayjitterpacket loss ratequality of servicereal-time application

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Unmanned Aerial Vehicle (UAV) networks face challenges in real-time video streaming due to the delay-reliability trade-off.
  • Buffer management and packet drop policies critically impact video quality in UAV networks.
  • Existing solutions struggle to balance performance demands for real-time, multi-source video delivery.

Purpose of the Study:

  • To introduce a novel reactive buffer management algorithm, MS-AL-ARQ, for real-time non-interactive video streaming in standalone UAV networks.
  • To enhance Quality of Service (QoS) by addressing packet loss and improving video data reception reliability.
  • To provide a robust solution for multi-source video streaming scenarios within UAV networks.

Main Methods:

  • Implementation of a selective-repeat Automatic Repeat Request (ARQ) model within a shared buffer system.
  • Integration of the MS-AL-ARQ algorithm at the application layer for packet reordering and recovery.
  • Real-time measurement of QoS metrics including packet loss rate, delay, and delay jitter for each data flow.

Main Results:

  • The MS-AL-ARQ algorithm effectively alleviates packet loss caused by wireless interference and collisions.
  • Demonstrated improvement in video data QoS under adverse network connection conditions.
  • Successful identification and detection of packet loss events, triggering Negative-Acknowledgments (NACKs).

Conclusions:

  • The proposed MS-AL-ARQ algorithm significantly enhances video streaming QoS in UAV networks.
  • The algorithm's performance was validated across various network conditions and node densities.
  • Identified and analyzed network congestion issues during performance evaluations, providing insights for future optimization.