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BAR: Blockwise Adaptive Recoding for Batched Network Coding.

Hoover H F Yin1,2, Shenghao Yang3, Qiaoqiao Zhou4

  • 1Department of Information Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.

Entropy (Basel, Switzerland)
|July 29, 2023
PubMed
Summary
This summary is machine-generated.

Blockwise adaptive recoding (BAR) improves throughput in multi-hop Internet of Things (IoT) networks by efficiently adapting to changing channel conditions. This practical solution offers significant gains even with imperfect channel knowledge.

Keywords:
adaptive recodingbatched network codinglinear network coding

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Multi-hop networks are crucial for emerging Internet of Things (IoT) applications.
  • Packet loss in these networks necessitates reliable communication solutions like Batched Network Coding (BNC).
  • BNC offers reduced computational and storage overhead compared to traditional random linear network coding.

Purpose of the Study:

  • To introduce and investigate Blockwise Adaptive Recoding (BAR), a practical recoding scheme for BNC.
  • To address implementation challenges of BAR on resource-constrained IoT devices.
  • To design and evaluate feedback schemes for BAR in imperfect feedback environments.

Main Methods:

  • BAR learns channel conditions from short observations for adaptive recoding.
  • Focus on efficient BAR algorithm implementation for low-power IoT devices.
  • Design and analysis of feedback mechanisms under noisy or incomplete feedback.

Main Results:

  • BAR demonstrates significant throughput gains with small batch sizes compared to existing schemes.
  • The performance improvement of BAR is robust and insensitive to inaccuracies in channel knowledge.
  • Numerical evaluations validate the effectiveness of BAR in dynamic channel environments.

Conclusions:

  • BAR is a practical and efficient solution for reliable communication in multi-hop IoT networks.
  • Its adaptability and robustness make it suitable for real-world IoT deployments with unknown or changing channel conditions.
  • BAR offers a viable alternative to existing recoding schemes, especially where computational resources are limited.