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Optimizing Merkle Tree Structure for Blockchain Transactions by a DC Programming Approach

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Computational Collective Intelligence (ICCCI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14162))

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Abstract

Merkle tree is a fundamental part of blockchain technology, especially in Ethereum cryptocurrency system. The balance of the accounts involved in each transaction is stored on the leaf nodes and must be updated in the State Merkle tree. In this paper, we take advantage of typical transaction characteristics for better constructing the Merkle tree to improve blockchain network performance. It consists of identifying a tree structure with the minimum number of hash values required to update the account data associated with each transaction based on the distribution of all transactions. The proposed optimization model is a combinatorial problem with quadratic functions and binary variables. By using the binary character of variables and penalty techniques, we provide a conventional DC (Difference of Convex functions) program that is efficiently solvable by the DCA (DC Algorithm). Additionally, we suggest an effective recursive DCA-based method for building a Merkle tree for a great amount of blockchain accounts. Numerical experiments on several datasets illustrate the efficiency of our approaches.

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Author information

Authors and Affiliations

  1. Département IA, LGIPM, Université de Lorraine, 57000, Metz, France

    Thi Tuyet Trinh Nguyen & Hoai An Le Thi

  2. Institut Universitaire de France (IUF), Paris, France

    Hoai An Le Thi

  3. Warwick Business School, University of Warwick, Coventry, CV4 7AL, UK

    Xuan Vinh Doan

Authors
  1. Thi Tuyet Trinh Nguyen
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  2. Hoai An Le Thi
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  3. Xuan Vinh Doan
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Corresponding author

Correspondence to Thi Tuyet Trinh Nguyen .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Eötvös Loránd University, Budapest, Hungary

    János Botzheim

  3. Eötvös Loránd University, Budapest, Hungary

    László Gulyás

  4. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Núñez

  5. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

  6. Universität Münster, Münster, Germany

    Gottfried Vossen

  7. Wrocław University of Science and Technology, Wrocław, Poland

    Adrianna Kozierkiewicz

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Nguyen, T.T.T., Le Thi, H.A., Doan, X.V. (2023). Optimizing Merkle Tree Structure for Blockchain Transactions by a DC Programming Approach. In: Nguyen, N.T., et al. Computational Collective Intelligence. ICCCI 2023. Lecture Notes in Computer Science(), vol 14162. Springer, Cham. https://doi.org/10.1007/978-3-031-41456-5_31

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  • DOI: https://doi.org/10.1007/978-3-031-41456-5_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41455-8

  • Online ISBN: 978-3-031-41456-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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