Skip to main content
Log in

Perpetual Network Coding for Delay Sensitive Applications

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Random Linear Network Coding (RLNC) is an erasure network coding technique used to improve communication and content distribution. However, RLNC is not efficient for data streaming applications, e.g., video streaming, where the data packets must be delivered in order and decoded within a tight deadline. Although some approaches have been proposed, these approaches have high computational complexity or require continuous feedback from the destination. Perpetual coding is an alternative approach which reduces the computational complexity and decrease per packet decoding delay at the destination. This paper focuses on improving decoding delay of communication systems by designing coding schemes based on Perpetual coding. Our simulation results demonstrate that the proposed schemes achieve a gain of \(67\%\) under a variety of channel conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Janus, H., Morten, V. P., Frank, H. P. F., & Torben, L. (2012). Network coding in the real world (pp. 87–114). Amsterdam: Elsevier.

    Google Scholar 

  2. Michael, L. (2002). LT codes. The 43rd Annual IEEE Symposium on Foundations of Computer Science 2002 Proceedings, 271–280.

  3. Amin, S. H. (2006). Raptor codes. IEEE Transactions on Information Theory, 52, 2551–2567.

    Article  MathSciNet  Google Scholar 

  4. Ralf, K., & Muriel, M. (2003). An algebraic approach to network coding. IEEE/ACM Transactions on Networking (TON), 11, 782–795.

    Article  Google Scholar 

  5. Mingchao, Y., Neda, A., & Parastoo, S. (2014). From instantly decodable to random linear network coded broadcast. IEEE Transactions on Communications, 62, 3943–3955.

    Article  Google Scholar 

  6. Petar, M., Nicholas, J.A.H., & Desmond, S.L. (2006). others, In: Proc. 44th Annual Allerton Conference on Communication, Control, and Computing, 482-491.

  7. Yee, W. L., & Marimuthu, P. (2008). Resilient network coding for wireless sensor networks. ICT-Mobile Summit 2008. IIMC International Information Management Corporation Ltd.

  8. Tracey, H., Muriel, M., Ralf, K., David, R. K., Michelle, E., Jun, S. H., & Ben, L. (2006). A random linear network coding approach to multicast. IEEE Transactions on Information Theory, 52(10), 4413–4430.

    Article  MathSciNet  Google Scholar 

  9. Danilo, S., Weifei, Z., & Frank, K. (2009). Sparse network coding with overlapping classes. Computing Research Repository - CORR, 74–79.

  10. Janus, H., Morten, V. P., Frank, H. P. F., & Muriel, M. (2011). On code parameters and coding vector representation for practical RLNC. In: 2011 IEEE International Conference on Communications (ICC). IEEE, 1–5.

  11. Soheil, F., Daniel, E. L., & Muriel, M. (2012). Tunable sparse network coding. In: 22th International Zurich Seminar on Communications. Eidgenossische Technische Hochschule Zurichs: IZS).

  12. Wen, L. C. H., Fang, L., & Yan, D. (2020). The decoding success probability of sparse random linear network coding for multicast. CoRR, abs-2010-05555. https://arxiv.org/abs/2010.05555.

  13. Wen, L. C. H., Fang, L., & Yan, D. (2021). Improved expression for rank distribution of sparse random linear network coding. IEEE Communications Letters, 25(5), 1472–1476.

  14. Hadi, S., & Peyman, P. (2020). An analytical model for the partial intercept probability in sparse linear network coding. IEEE Communications Letters, IEEE, 24(4), 725–728.

    Article  Google Scholar 

  15. Amir, Z., Peyman, P., & Mansoor, D. (2018). On the partial decoding delay of sparse network coding. IEEE Communications Letters, 22(8), 1668–1671.

    Article  Google Scholar 

  16. Amir, Z., Peyman, P., & Daniel, E. L. (2020). An analytical model for sparse network codes: Field size considerations. IEEE Access, 8, 78293–78314.

    Article  Google Scholar 

  17. Tracey, H., Ralf, K., Muriel, M., David, R. K., & Michelle, E. (2003). The benefits of coding over routing in a randomized setting. IEEE International Symposium on Information Theory 2003. Proceedings, 442.

  18. Mohammad, K., Douglas, L., Jason, C., & Muriel, M. (2017). Design of FEC for low delay in 5g. IEEE Journal on Selected Areas in Communications, 35(8), 1783–1793.

    Article  Google Scholar 

  19. Jason, C., & Muriel, M. (2015). Network coding over SATCOM: Lessons learned. In: International Conference on Wireless and Satellite Systems, Springer, 272–285.

  20. Mohammad, K., & Douglas, J.L. (2014). Low delay random linear coding over a stream, communication, control, and computing (Allerton). In: 2014 52nd Annual Allerton Conference on, IEEE, 521–528.

  21. Simon, W., Frank, G., Sreekrishna, P., Frank, H. P. F., & Martin, R. (2017). Caterpillar RLNC (CRLNC): A practical finite sliding window RLNC approach. IEEE Access, 5, 20183–20197.

    Article  Google Scholar 

  22. Jason, C., Douglas, L., & Muriel, M. (2015). A coded generalization of selective repeat ARQ. In: 2015 IEEE Conference on Computer Communications (INFOCOM), IEEE, 2155–2163.

  23. Eleni, D., Lorenzo, K., & Christina, F. (2013). Physical communication (pp. 100–113). Amsterdam: Elsevier.

    Google Scholar 

  24. Yunfeng, L., Ben, L., & Baochun, L. (2010). SlideOR: Online opportunistic network coding in wireless mesh networks, INFOCOM. In: 2010 Proceedings. IEEE, 1–5.

  25. Jay, K. S., Devavrat, S. H., Muriel, M., Szymon, J., Michael, M., & Joao, B. (2011). Network coding meets TCP: Theory and implementation. Proceedings of the IEEE, 99(3), 490–512.

    Article  Google Scholar 

  26. Tuan, T.T, Emmanuel, L., Jeromi, L. (2012). Online multipath convolutional coding for real-time transmission, arXiv preprint arXiv:1204.1428.

  27. Jonathan, D., Emmanuel, L., Jeromi, L., & Vincent, R. (2015). Tetrys, an on-the-fly network coding Protocol. hal-01089745v3. https://hal.inria.fr/hal-01089745v3.

  28. Paresh, S. (2015). Systematic network coding for lossy line networks, Universitat Autonoma de Barcelona.

  29. Vu, N., Elif, T., Giang, T. N., Daniel, E. L., Frank, H. P. F., & Martin, R. (2020). DSEP fulcrum: Dynamic sparsity and expansion packets for fulcrum network coding. IEEE Access, 8, 78293–78314.

    Article  Google Scholar 

  30. Janus, H., Morten, V.P., Frank, H.P.F., & Muriel, M. (2014). Vehicular Technology Conference, IEEE 1–6.

  31. Peyman, P., Sergio, C., & Daniel, E. L. (2016). An analytical model for perpetual network codes in packet erasure channels. International Workshop on Multiple Access Communications-Springer, 10121(10), 126–135.

  32. Ahmed, D., Sameh, S., Tareq, Y. A. N., & Mohamed, S. A. (2014). A lossy graph model for delay reduction in generalized instantly decodable network coding. IEEE, 3(3), 281–284.

    Google Scholar 

  33. Lu, L., Ming, X., & Lars, K. R. (2011). Design and analysis of relay-aided broadcast using binary network codes. Karnataka: Academy Publisher.

    Book  Google Scholar 

  34. Sameh, S., Ahmed, D., Shahrokh, V., Tareq, A. N., & Mohamed, S. A. (2014). Partially blind instantly decodable network codes for lossy feedback environment. IEEE Transactions on Wireless Communications, 13(9), 4871–4883.

    Article  Google Scholar 

  35. Ahmed, D., Sameh, S., Mohamed, S.A., & Tareq, Y. (2013). Delay reduction in lossy intermittent feedback for generalized instantly decodable network coding. In: 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob),IEEE, 388–393.

  36. Neda, A., Parastoo, S., & Sameh, S. (2014). Enabling a tradeoff between completion time and decoding delay in instantly decodable network coded systems. IEEE Transactions on Communications, 62(4), 1296–1309.

    Article  Google Scholar 

  37. Szymon, C. H., Michael, J., Sachin, K., & Dina, K. (2007). Trading structure for randomness in wireless opportunistic routing. ACM, 37(4), 169–180.

    Google Scholar 

  38. Pablo, G., Daniel, E. L., & Ramon, A. (2017). Markov chain model for the decoding probability of sparse network coding. IEEE Transactions on Communications, 65(4), 675–1685.

    Google Scholar 

  39. Mingchao, Yu., Neda, A., & Parastoo, S. (2014). From instantly decodable to random linear network coded broadcast. IEEE Transactions on Communications, 62(11), 3943–3955.

    Article  Google Scholar 

  40. Enrico, M., Mea, W., Pascal, F., & Athina, M. (2013). Network coding meets multimedia: A review. IEEE Trans Multimedia, 15(5), 1195–1212.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by the Aarhus Universitets Forskningsfond Starting Grant Project AUFF- 2017-FLS-7-1, and Aarhus University’s DIGIT Centre.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peyman Pahlevani.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mohammadi, S., Pahlevani, P. & Lucani, D.E. Perpetual Network Coding for Delay Sensitive Applications. Wireless Pers Commun 120, 923–947 (2021). https://doi.org/10.1007/s11277-021-08497-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08497-x

Keywords

Navigation