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Novel compressed linear network coding vectors for multihop communication networks

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Abstract

Random Linear Network Coding (RLNC) is well-known to provide high throughput and low latency for vast communication networks. However, RLNC often suffers from high coefficients overhead, specifically, when it’s applied to limited resource or short-packet networks. Herein, the problem of RLNC coefficients vector overhead is revisited. A novel framework, based on modular arithmetic and prime numbers, and influenced by the Chinese remainder theorem (CRT), is proposed to reduce the coefficients overhead by augmenting only a tiny one item coefficient instead of the entire coefficients vector. The proposed method successfully addresses all the shortcomings of previous methods, including restrictions on generation size and packet density, recoding on intermediate nodes, and creating innovative coding vectors. Theoretical analysis and experimental demonstrate the superior performance of the proposed scheme in terms of coefficients overhead ratio, download time, throughput, and packet drop rate. This evaluation has considered two types of networks: wireless sensors network for Internet of things, and conventional wireline Ethernet.

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Notes

  1. https://www.comsoc.org/publications/ctn/coding-network-next-generation-coding-flexible-network-operation.

  2. However, the adjustment of the framework to provide secure communication is beyond the paper scope and is highlighted as a future work.

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Acknowledgements

The authors would like to acknowledge the support provided by King Fahd University of Petroleum and Minerals (KFUPM), Interdisciplinary Research Center for Intelligent Secure Systems (IRC-ISS), and the department of Computer Engineering.

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The authors have not disclosed any funding.

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Authors and Affiliations

  1. Interdisciplinary Research Center for Intelligent Secure Systems, King Fahd University of Petroleum and Minerals, Dhahran, Eastern Province, 31261, Saudi Arabia

    Anas A. Abudaqa & Alawi A. ALsaggaf

  2. Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Ashraf S. H. Mahmoud & Tarek R. Sheltami

  3. Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Ashraf S. H. Mahmoud & Tarek R. Sheltami

  4. Mathematical Sciences Department, DCC, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Alawi A. ALsaggaf

Authors
  1. Anas A. Abudaqa
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  2. Ashraf S. H. Mahmoud
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  3. Alawi A. ALsaggaf
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  4. Tarek R. Sheltami
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Contributions

Anas developed the idea of the proposed framework, implemented the code and prepared the experiments, and wrote the manuscript. Ashraf participated in the mathematical and probabilistic model, performed data analysis and interpreted the results, and reviewed the manuscript. Alawi participated in the mathematical analysis and proofs. Tarek reviewed the manuscript, and gave some advices and instructions.

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Correspondence to Anas A. Abudaqa.

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Abudaqa, A.A., Mahmoud, A.S.H., ALsaggaf, A.A. et al. Novel compressed linear network coding vectors for multihop communication networks. Telecommun Syst (2024). https://doi.org/10.1007/s11235-024-01110-z

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