Towards Scalable Blockchain: Adaptive Tree Algorithms for Data Verification and Storage by@restructure
Towards Scalable Blockchain: Adaptive Tree Algorithms for Data Verification and Storage
by Restructure TechnologiesSeptember 10th, 2024
Too Long; Didn't Read
This work introduces an adaptive restructuring algorithm for Merkle and Verkle Trees, improving blockchain scalability and efficiency in data verification and storage. It demonstrates the algorithm's versatility across different blockchain architectures.
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
1.1. The Blockchain Paradigm and the Challenge of Scalability
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
6.2. 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
8.2. Technology and Advantages
9.2. Comparison with Existing Solutions
1.3. Our contribution
This work introduces a novel approach to optimizing tree-based data structures within blockchain technology, focusing on adaptive restructuring techniques for Merkle and Verkle Trees. Our contributions are twofold: First, we propose a dynamic restructuring algorithm that enhances the scalability and efficiency of blockchain systems by optimizing the verification and storage processes. Second, we extend the applicability of these optimized tree structures beyond traditional blockchain applications, demonstrating their versatility in various blockchain architectures and scenarios. Through rigorous analysis and experimentation, our research addresses the critical scalability challenges faced by blockchain technology, offering a scalable, efficient, and adaptable solution.
1.4. Article structure
The structure of this article is designed to provide a comprehensive overview of our research and findings. Section 2 conceptualizes the problem of blockchain scalability and the role of tree-based data structures in addressing this challenge. Section 3 introduces our idea for optimizing trees in blockchain, detailing the theoretical foundation of our approach. Section 4 evaluates the efficiency of adaptive Merkle trees through analytical and empirical methods. Section 5 describes the algorithm for Merkle Tree restructuring, followed by Section 6, which presents examples of the algorithm's execution in various scenarios. Section 7 delves into the specifics of path encoding in adaptive Merkle Trees, and Section 8 explores the enhancement of Verkle Trees through adaptive restructuring. The discussion in Section 9 synthesizes our results, comparing them with existing solutions and highlighting our contribution to the field. Finally, the conclusion in Section 10 summarizes our research contributions and outlines future directions for this promising area of study.
This paper is available on arxiv under CC by 4.0 Deed (Attribution 4.0 International) license.
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