paint-brush
How Adaptive Tree Structures Tackle Blockchain Scalability Issuesby@restructure
110 reads

How Adaptive Tree Structures Tackle Blockchain Scalability Issues

by Restructure TechnologiesSeptember 11th, 2024
Read on Terminal Reader
Read this story w/o Javascript
tldt arrow

Too Long; Didn't Read

This article explores innovative approaches to improving blockchain scalability by optimizing Merkle trees, addressing the limitations of static structures and existing scalability solutions.
featured image - How Adaptive Tree Structures Tackle Blockchain Scalability Issues
Restructure Technologies HackerNoon profile picture

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.

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. Discussion

In this work, we have embarked on a comprehensive exploration of optimizing tree structures within the blockchain ecosystem, addressing the critical challenge of scalability that plagues current blockchain technologies. Our investigation spans from conceptualizing the inherent problems associated with traditional Merkle trees to proposing and validating an innovative approach for adaptive restructuring of these trees to enhance efficiency and scalability in blockchain systems.


The blockchain paradigm, while revolutionary, faces significant scalability challenges, primarily due to the inherent limitations of its underlying data structures and consensus mechanisms. Traditional Merkle trees, despite their widespread adoption for ensuring data integrity and facilitating efficient verifications, contribute to these scalability issues due to their static nature and the increasing cost of operations as the blockchain grows.


Existing solutions to blockchain scalability, such as sharding and layer 2 protocols, offer partial remedies by distributing the workload or offloading transactions. However, these approaches often introduce complexity or compromise on decentralization and security. Our review of the state of the art highlights a gap in dynamically optimizing the data structures themselves to directly address the root causes of inefficiency.


This paper is available on arxiv under CC by 4.0 Deed (Attribution 4.0 International) license.