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Adaptive Merkle Trees and Their Impact on Blockchain Scalability

by Restructure TechnologiesSeptember 11th, 2024

Too Long; Didn't Read

We introduce adaptive Merkle trees that optimize blockchain efficiency through dynamic restructuring, reducing computational costs. Our method also enhances Verkle trees, showcasing its impact on large-scale blockchain applications.

featured image - Adaptive Merkle Trees and Their Impact on Blockchain Scalability

Authors:

(1) Oleksandr Kuznetsov, Proxima Labs, 1501 Larkin Street, suite 300, San Francisco, USA and Department of Political Sciences, Communication and International Relations, University of Macerata, Via Crescimbeni, 30/32, 62100 Macerata, Italy ([email protected]);

(2) Dzianis Kanonik, Proxima Labs, 1501 Larkin Street, suite 300, San Francisco, USA;

(3) Alex Rusnak, Proxima Labs, 1501 Larkin Street, suite 300, San Francisco, USA ([email protected]);

(4) Anton Yezhov, Proxima Labs, 1501 Larkin Street, suite 300, San Francisco, USA;

(5) Oleksandr Domin, Proxima Labs, 1501 Larkin Street, suite 300, San Francisco, USA.

Table of Links

Abstract and 1. Introduction

1.1. The Blockchain Paradigm and the Challenge of Scalability

1.2. State of the art

1.3. Our contribution and 1.4. Article structure

2. Conceptualizing the Problem

3. Our Idea for Optimizing Trees in Blockchain

4. Efficiency of adaptive Merkle trees

5. Algorithm for Merkle Tree Restructuring

6. Examples of Merkle Tree Restructuring Algorithm Execution and 6.1 Example 1: Restructuring a Binary Tree by Adding One Leaf

6.2. Example 1.1: Binary Tree Restructuring Through Leaf Node Swapping

6.3. Example 2.1: Restructuring a Non-Binary Tree by Adding a Single Leaf

6.4. Example 2.2: Restructuring a Non-Binary Tree Through Leaf Pair Swapping

6.5. Example 2.3: Restructuring a Patricia-Merkle Tree Fragment Through Leaf Pair Swapping

7. Path Encoding in the Adaptive Merkle Tree

8. Enhancing Verkle Trees Through Adaptive Restructuring and 8.1. Application of Adaptive Trees in Verkle Tree Technology

8.2. Technology and Advantages

9. Discussion

9.1. Our Contribution

9.2. Comparison with Existing Solutions

10. Conclusion and References

9.1. Our Contribution

Our primary contribution lies in the introduction of adaptive Merkle trees, a novel concept that leverages dynamic restructuring based on usage patterns to optimize path lengths and reduce the computational overhead associated with data verification and integrity checks. By applying principles from Huffman and Shannon-Fano coding to the organization of tree nodes, we ensure that frequently accessed data is more accessible, thereby reducing the average path length and associated costs.

Through rigorous analysis and examples, we demonstrated the efficiency gains achievable with adaptive Merkle trees. Our algorithm for Merkle tree restructuring, detailed in Section 5, provides a systematic approach for dynamically adjusting tree structures, significantly improving upon the static nature of traditional Merkle trees.

Extending our concept to Verkle trees, we showcased how adaptive restructuring could be applied to this advanced data structure, further enhancing its efficiency and making it even more suitable for large-scale blockchain applications. This application not only underscores the versatility of our approach but also its potential to contribute to the next generation of blockchain technologies.