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SE-Chain: A Scalable Storage and Efficient Retrieval Model for Blockchain

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Abstract

Massive data is written to blockchain systems for the destination of keeping safe. However, existing blockchain protocols still demand that each full node has to contain the entire chain. Most nodes quit because they are unable to grow their storage space with the size of data. As the number of nodes decreases, the security of blockchains would significantly reduce. We present SE-Chain, a novel scale-out blockchain model that improves storage scalability under the premise of ensuring safety and achieves efficient retrieval. The SE-Chain consists of three parts: the data layer, the processing layer and the storage layer. In the data layer, each transaction is stored in the AB-M tree (Adaptive Balanced Merkle tree), which adaptively combines the advantages of balanced binary tree (quick retrieval) and Merkle tree (quick verification). In the processing layer, the full nodes store the part of the complete chain selected by the duplicate ratio regulation algorithm. Meanwhile, the node reliability verification method is used for increasing the stability of full nodes and reducing the risk of imperfect data recovering caused by the reduction of duplicate number in the storage layer. The experimental results on real datasets show that the query time of SE-Chain based on the AB-M tree is reduced by 17% when 16 nodes exist. Overall, SE-Chain improves the storage scalability extremely and implements efficient querying of transactions.

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References

  1. Chen W L, Zheng Z B, Cui J H, Ngai E C H, Zheng P L, Zhou Y R. Detecting Ponzi schemes on Ethereum: Towards healthier blockchain technology. In Proc. the 2018 World Wide Web Conference on World Wide Web, April 2018, pp.1409-1418. DOI: 10.1145/3178876.3186046.

  2. Vo H T, Kundu A, Mohania M K. Research directions in blockchain data management and analytics. In Proc. the 21st International Conference on Extending Database Technology, March 2018, pp.445-448. DOI: 10.5441/002/edbt.2018.43.

  3. Eyal I, Gencer A E, Sirer E G, van Renesse R. Bitcoin-NG: A scalable blockchain protocol. In Proc. the 13th USENIX Symposium on Networked Systems Design and Implementation, March 2016, pp.45-59.

  4. Yong Y,Wang F Y. Blockchain: The state of the art and future trends. Acta Automatica Sinica, 2016, 42(4): 481-494. DOI: 10.16383/j.aas.2016.c160158. (in Chinese)

  5. Bonneau J, Miller A, Clark J, Narayanan A, Kroll J A, Felten E W. SoK: Research perspectives and challenges for Bitcoin and cryptocurrencies. In Proc. the 2015 IEEE Symposium on Security and Privacy, May 2015, pp.104-121. DOI: 10.1109/SP.2015.14.

  6. Henry R, Herzberg A, Kate A. Blockchain access privacy: Challenges and directions. IEEE Security and Privacy, 2018, 16(4): 38-45. DOI: https://doi.org/10.1109/MSP.2018.3111245.

    Article  Google Scholar 

  7. Li J R, Wolf T. A one-way proof-of-work protocol to protect controllers in software-de_ned networks. In Proc. the 2016 Symposium on Architectures for Networking and Communications Systems, March 2016, pp.123-124. DOI: 10.1145/2881025.2889481.

  8. Jia D Y, Xin J C, Wang Z Q, Guo W, Wang G R. ElasticChain: Support very large Blockchain by reducing data redundancy. In Proc. the 2nd International Joint Conference on Web and Big Data, July 2018, pp.440-454. DOI: 10.1007/978-3-319-96893-3 33.

  9. Al-Bassam M, Sonnino A, Bano S, Hrycyszyn D, Danezis G. Chainspace: A sharded smart contracts platform. In Proc. the 25th Annual Network and Distributed System Security Symposium, February 2018. DOI: 10.14722/ndss.2018.23244.

  10. Zamani M, Movahedi M, Raykova M. RapidChain: Scaling blockchain via full sharding. In Proc. the 2018 ACM SIGSAC Conference on Computer and Communications Security, October 2018, pp.931-948. DOI: 10.1145/3243734.3243853.

  11. Xu Z H, Han S Y, Chen L. CUB, a consensus unit-based storage scheme for Blockchain system. In Proc. the 34th IEEE International Conference on Data Engineering, April 2018, pp.173-184. DOI: 10.1109/ICDE.2018.00025.

  12. Luu L, Narayanan V, Zheng C D, Baweja K, Gilbert S, Saxena P. A secure sharding protocol for open blockchains. In Proc. the 2016 ACM SIGSAC Conference on Computer and Communications Security, October 2016, pp.17-30. DOI: 10.1145/2976749.2978389.

  13. Xu C, Zhang C, Xu J L. vChain: Enabling verifiable Boolean range queries over blockchain databases. In Proc. the 2019 International Conference on Management of Data, June 2019, pp.141-158. DOI: 10.1145/3299869.3300083.

  14. Zhang C, Xu C, Xu J L, Tang Y Z, Choi B. GEM2-Tree: A gas-efficient structure for authenticated range queries in blockchain. In Proc. the 35th IEEE International Conference on Data Engineering, April 2019, pp.842-853. DOI: 10.1109/ICDE.2019.00080.

  15. Third A, Domingue J. Linked data indexing of distributed ledgers. In Proc. the 26th International Conference on World Wide Web Companion, April 2017, pp.1431-1436. DOI: 10.1145/3041021.3053895.

  16. Li Y, Zheng K, Yan Y, Liu Q, Zhou X F. EtherQL: A query layer for blockchain system. In Proc. the 22nd International Conference on Database Systems for Advanced Applications, March 2017, pp.556-567. DOI: 10.1007/978-3-319-55699-4 34.

  17. Wang S, Dinh T T A, Lin Q, Xie Z L, Zhang M H, Cai Q C, Chen G, Ooi B C, Ruan P C. ForkBase: An efficient storage engine for blockchain and forkable applications. Proceedings of the VLDB Endowment, 2018, 11(10): 1137-1150. DOI: 10.14778/3231751.3231762.

  18. Jia D Y, Xin J C, Wang Z Q, Guo W, Wang G R. Efficient query model for storage capacity scalable Blockchain system. Journal of Software, 2019, 30(9): 91-106. DOI: 10.13328/j.cnki.jos.005774. (in Chinese)

  19. Baudin É. Probabilities and Life. Dover Publications Inc, 1962.

  20. Yu H F, Gibbons P B, Kaminsky M, Xiao F. SybilLimit: A near-optimal social network defense against sybil attacks. IEEE/ACM Transactions on Networking, 2010, 18(3): 885-898. DOI: https://doi.org/10.1109/TNET.2009.2034047.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Da-Yu Jia & Jun-Chang Xin

  2. Key Laboratory of Big Data Management and Analytics of Liaoning Province, Shenyang, 110819, China

    Jun-Chang Xin

  3. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China

    Zhi-Qiong Wang

  4. Neusoft Institute of Intelligent Healthcare Technology Co.Ltd., Shenyang, 110179, China

    Zhi-Qiong Wang

  5. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Han Lei

  6. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China

    Guo-Ren Wang

Authors
  1. Da-Yu Jia
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  2. Jun-Chang Xin
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  3. Zhi-Qiong Wang
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  4. Han Lei
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  5. Guo-Ren Wang
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Corresponding author

Correspondence to Jun-Chang Xin.

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Jia, DY., Xin, JC., Wang, ZQ. et al. SE-Chain: A Scalable Storage and Efficient Retrieval Model for Blockchain. J. Comput. Sci. Technol. 36, 693–706 (2021). https://doi.org/10.1007/s11390-020-0158-2

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  • DOI: https://doi.org/10.1007/s11390-020-0158-2

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