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 (kuznetsov@karazin.ua);
(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 (alex@proxima.one);
(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
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.