Skip to main content

Research on Composite Index Construction Method Based on Master-Slave Blockchain Structure

  • Conference paper
  • First Online:
Web and Big Data. APWeb-WAIM 2022 International Workshops (APWeb-WAIM 2022)

Abstract

Blockchain is a new information processing technology that uses efficient cryptographic principles for the trustworthy storage of big data. With the exponential growth of the scale of data on the chain, the problems of low query efficiency and long traceability time of the existing blockchain system become more and more serious. To solve the above problems, this paper proposes a composite index construction method based on a master-slave blockchain structure. Firstly, a weight matrix is introduced to slice the whole master-slave blockchain based on the master chain structure; secondly, a master index construction method based on jump consistency hash is proposed for the master blockchain within each slice; finally, based on an improved Bloom filter, a slave composite index is constructed for each master block corresponding to the slave blockchain. Experimental results show that, compared with the existing methods, the proposed method can reduce the index construction time by 4.63% on average, improve the query efficiency by 6.71%, and reduce the memory overhead by 24.4%.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Zhu, J.M., Zhagn, Q.N., Gao, S., Ding, Q.Y., Yuan, L.P., et al.: Blockchain-based trusted federated learning model for privacy protection. Chin. J. Comput. 44(12), 2464–2484 (2021)

    Google Scholar 

  2. Li, C., Li, P., Zhou, D., et al.: A decentralized blockchain with high throughput and fast confirmation. In: 2020 {USENIX} Annual Technical Conference ({USENIX}{ATC} 2020), pp. 515–528 (2020)

    Google Scholar 

  3. Połap, D., Srivastava, G., Jolfaei, A., et al.: Blockchain technology and neural networks for the internet of medical things. In: IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 508–513. IEEE (2020)

    Google Scholar 

  4. Wei, S.J., Li, S.S., Wanag, J.H.: Cross-domain authentication protocols based on identity cryptosystems and blockchains. Chin. J. Comput. 44(05), 908–920 (2021)

    Google Scholar 

  5. Bao, J., He, D., Luo, M., et al.: A survey of blockchain applications in the energy sector. IEEE Syst. J. 15(3), 3370–3381 (2020)

    Article  Google Scholar 

  6. Kalodner, H., Möser, M., Lee, K., et al.: {BlockSci}: design and applications of a blockchain analysis platform. In: 29th USENIX Security Symposium (USENIX Security 2020), pp. 2721–2738 (2020)

    Google Scholar 

  7. Huang, J., Kong, L., Chen, G., et al.: Towards secure industrial IoT: blockchain system with credit-based consensus mechanism. IEEE Trans. Industr. Inf. 15(6), 3680–3689 (2019)

    Article  Google Scholar 

  8. Sui, Y., Wang, W., Deng, X.: High throughput verifiable query method for blockchain-oriented off-chain database. J. Chin. Comput. Syst. 42(6), 1304–1312 (2021)

    Google Scholar 

  9. Cai, L., Zhu, Y.C., Guo, Q.X., Zhang, Z., Jin, C.Q.: Efficient materialized view maintenance and trusted query for blockchain. J. Softw. 31(3), 680–694 (2020)

    Google Scholar 

  10. Nathan, V., Ding, J., Alizadeh, M., Kraska, T.: Learning multi-dimensional indexes. In: 2020 ACM SIGMOD International Conference on Management of Data (SIGMOD 2020), 14–19 June 2020, Portland, OR, USA, 16 p. ACM, New York (2020)

    Google Scholar 

  11. XiaoJu, H., XueQing, G., ZhiGang, H., et al.: Ebtree: a b-plus tree based index for Ethereum blockchain data. In: Proceedings of the 2020 Asia Service Sciences and Software Engineering Conference, pp. 83–90 (2020)

    Google Scholar 

  12. Kipf, A., Marcus, R., van Renen, A., et al.: RadixSpline: a single-pass learned index. In: Proceedings of the Third International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, pp. 1–5 (2020)

    Google Scholar 

  13. Xing, X., Chen, Y., Li, T., et al.: A blockchain index structure based on subchain query. J. Cloud Comput. 10(1), 1–11 (2021)

    Article  Google Scholar 

  14. Alghamdi, N., Zhang, L., Zhang, H., et al.: ChainLink: indexing big time series data for long subsequence matching. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 529–540. IEEE (2020)

    Google Scholar 

  15. Gao, Y.N., Ye, J.B., Yang, N.Z., Gao, X.F., Chen, G.H.: Middle layer-based scalable learned index scheme. J. Softw. 31(3), 620−633 (2020)

    Google Scholar 

Download references

Acknowledgment

This study was supported by the Applied Basic Research Program of Liaoning Province (No. 2022JH2/101300250); the Digital Liaoning Smart Building Strong Province (Direction of Digital Economy) (No.13031307053000568); the National Key R&D Program of China (No. 2021YFF0901004); the Central Government Guides Local Science and Technology Development Foundation Project of Liaoning Province (No. 2022JH6/100100032); the Natural Science Foundation of Liaoning Province (No. 2022-KF-13-06).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tingwei Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, G., Sui, Y., Zhang, J., Liu, C., Hu, W., Chen, T. (2023). Research on Composite Index Construction Method Based on Master-Slave Blockchain Structure. In: Yang, S., Islam, S. (eds) Web and Big Data. APWeb-WAIM 2022 International Workshops. APWeb-WAIM 2022. Communications in Computer and Information Science, vol 1784. Springer, Singapore. https://doi.org/10.1007/978-981-99-1354-1_8

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-1354-1_8

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-1353-4

  • Online ISBN: 978-981-99-1354-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics