Improve Blockchain Performance using Graph Data Structure and Parallel Mining

TL;DR

This paper introduces GraphChain, a graph-based blockchain model combined with parallel mining to enhance capacity and performance, addressing inefficiencies in traditional blockchain systems like Bitcoin.

Contribution

It proposes a novel graph data structure for blockchain and a parallel mining approach, improving resource utilization and scalability.

Findings

GraphChain increases blockchain capacity.

Parallel mining reduces mining time.

Simulation shows performance improvements.

Abstract

Blockchain technology is ushering in another break-out year, the challenge of blockchain still remains to be solved. This paper analyzes the features of Bitcoin and Bitcoin-NG system based on blockchain, proposes an improved method of implementing blockchain systems by replacing the structure of the original chain with the graph data structure. It was named GraphChain. Each block represents a transaction and contains the balance status of the traders. Additionally, as everyone knows all the transactions in Bitcoin system will be baled by only one miner that will result in a lot of wasted effort, so another way to improve resource utilization is to change the original way to compete for miner to election and parallel mining. Researchers simulated blockchain with graph structure and parallel mining through python, and suggested the conceptual new graph model which can improve both capacity and performance.