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Data Transmission Scheme Considering Node Failure for Blockchain

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Abstract

In recent years, Blockchain technology has attracted considerable attention from the industrial circle. Blockchain is a distributed ledger technology, which must be validated, stored and maintained by all nodes to ensure data security, transparency, and integrity. The communication efficiency of Blockchain is an important factor restricting its application. Existing algorithms can provide data routing schemes for Blockchain but without considering the node failure. On Blockchain, node failure is a common phenomenon due to the nodes’ selfishness and nodes’ mobility. Node failure degrades the network performance or even sometimes makes the network useless. This paper proposes a data transmission scheme considering node failure for finishing validation of block data on Blockchain, which firstly sets response threshold level to detect failure node, and then using greedy idea constructs communication tree to organize all nodes forwarding block data. Based to the multi-link concurrent communication tree model, this scheme maximizes the potential transmitting capacity of nodes and assigns proper tasks to other nodes beside source node, so it can shorten the validation time of Blockchain transaction, and improve resistance to node failure. Theoretical proof and experimental results show the effectiveness and the efficiency of the proposed data transmission scheme.

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References

  1. Godsiff, P. (2015). Bitcoin: Bubble or blockchain (pp. 191–203). Agent and Multi-agent Systems: Technologies and Applications.

    Google Scholar 

  2. Kraft, D. (2016). Difficulty control for blockchain-based consensus systems. Peer-to-Peer Networking and Applications, 9(2), 397–413.

    Article  Google Scholar 

  3. Swan, M. (2015). Blockchain thinking: The brain as a decentralized autonomous corporation. IEEE Technology and Society Magazine, 34(4), 41–52.

    Article  Google Scholar 

  4. Eldred, M. (2016). Blockchain thinking and euphoric hubris. IEEE Technology and Society Magazine, 35(2), 27–27.

    Article  MathSciNet  Google Scholar 

  5. Zyskind, G., Nathan, O., & Pentland, A. S. (2015). Decentralizing privacy: Using blockchain to protect personal data. In IEEE security and privacy workshops (pp. 180–184).

  6. Wilson, D., & Ateniese, G. (2015). From pretty good to great: Enhancing PGP using bitcoin and the blockchain. In International conference on network and system security (pp. 368–375).

    Chapter  Google Scholar 

  7. Kypriotaki, K., Zamani, E., & Giaglis, G. (2015). From bitcoin to decentralized autonomous corporations. In: International conference on enterprise information systems (pp. 284–290).

  8. Hurlburt, G. (2016). Might the blockchain outlive bitcoin? IEEE Educational Activities Department, 18(2), 12–16.

    Google Scholar 

  9. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf.

  10. Reijers, W., & Coeckelbergh, M. (2016). The blockchain as a narrative technology: Investigating the social ontology and normative configurations of cryptocurrencies. Philosophy & Technology. https://doi.org/10.1007/s13347-016-0239-x.

    Article  Google Scholar 

  11. Kumar, S., & Mehfuz, S. (2016). Intelligent probabilistic broadcasting in mobile ad hoc network: A PSO approach. Journal of Reliable Intelligent Environments, 2(2), 1–9.

    Article  Google Scholar 

  12. He, M., Zhang, Y. J., & Meng, X. W. (2015). Resource location flooding strategy of unstructured P2P for user requirements. Journal of Software, 26(2), 640–662.

    MathSciNet  Google Scholar 

  13. Viana, D. (2016). Two technical images: Blockchain and high-frequency trading. Philosophy & Technology. https://doi.org/10.1007/s13347-016-0247-x.

    Article  Google Scholar 

  14. Pai, V., Kumar, K., Tamilmani, K., Sambamurthy, V., & Mohr, A. E. (2005). Chainsaw: Eliminating trees from overlay multicast. In International conference on peer-to-peer systems (pp. 127–140).

  15. Biskupski, B., Schiely, M., Felber, P., & Meier, R. (2008). Tree-based analysis of mesh overlays for peer-to-peer streaming. In Ifip Wg 6.1 international conference on distributed applications and interoperable systems (pp. 126–139).

  16. Liu, T. S., & Zhao, S. Z. (2007). P2P Distributed Database System. Beijing: Science Press.

    Google Scholar 

  17. Li, J., & Liu, T. S. (2010). Study on a P2P communication tree algorithm based on multi-link. Journal of Northwest University, 40(6), 970–974.

    Google Scholar 

  18. Li, J., Liang, G. Q., & Liu, T. S. (2017). A novel multi-link integrated factor algorithm considering node trust degree for blockchain-based communication. KSII Transactions on Internet & Information Systems, 11(8), 3766–3788.

    Google Scholar 

  19. Huang, J., Fan, X., Wan, M., Zhuo, Z., Yang, Y., & Chen, S. (2016). Stable cluster-based routing protocol for mobile ad hoc networks. Journal of Beijing University of Aeronautics & Astronautics, 42(11), 2332–2339.

    Google Scholar 

  20. Jia, G., Fu, X. D., Gao, T. Y., Chen, B. B., & Fan, H. B. (2014). A survey on the node failure handling of P2P networks. In Control and decision conference (pp. 4077–4082).

  21. Ranga, V., Dave, M., & Verma, A. K. (2014). A hybrid timer based single node failure recovery approach for WSANs. Wireless Personal Communications, 77(3), 2155–2182.

    Article  Google Scholar 

  22. Uwitonze, A., Huang, J., Ye, Y., & Cheng, W. (2017). Connectivity restoration in wireless sensor networks via space network coding. Sensors, 17(4), 902.

    Article  Google Scholar 

  23. Boudries, A., Amad, M., & Siarry, P. (2016). Novel approach for replacement of a failure node in wireless sensor network. Telecommunication Systems, 65, 1–10.

    Google Scholar 

  24. Wang, H., Ding, X., Huang, C., & Wu, X. (2016). Adaptive connectivity restoration from node failure(s) in wireless sensor networks. Sensors, 16(10), 1487.

    Article  Google Scholar 

  25. Liu, X., & Medhi, D. (2017). Optimally selecting standby virtual routers for node failures in a virtual network environment. IEEE Transactions on Network and Service Management, 14(2), 275–288.

    Article  Google Scholar 

  26. Shahriar, N., Ahmed, R., Chowdhury, S., Khan, A., Boutaba, R., & Mitra, J. (2017). Generalized recovery from node failure in virtual network embedding. IEEE Transactions on Network and Service Management, 14(9), 261–274.

    Article  Google Scholar 

  27. Abdullah, S., & Yang, K. (2014). An energy efficient message scheduling algorithm considering node failure in IoT environment. Wireless Personal Communications, 79(3), 1815–1835.

    Article  Google Scholar 

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Acknowledgements

This work was supported by Natural Science Foundation of China (Grant: 5170715), Scientific Research Foundation of Education Bureau of Shaanxi Province (Grant: 15JK1571) and Science & Technology Brainstorm Project of Shaanxi Province (Grant: 2016GY132).

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Correspondence to Jiao Li.

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Li, J. Data Transmission Scheme Considering Node Failure for Blockchain. Wireless Pers Commun 103, 179–194 (2018). https://doi.org/10.1007/s11277-018-5434-x

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  • DOI: https://doi.org/10.1007/s11277-018-5434-x

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