High-efficiency Blockchain-based Supply Chain Traceability

TL;DR

This paper addresses the efficiency challenges in blockchain-based supply chain traceability by proposing a parallel search method with bipartite graph modeling, significantly reducing search time overhead.

Contribution

It introduces a novel parallel search approach and bipartite graph model to improve efficiency in blockchain supply chain traceability, a previously understudied aspect.

Findings

Time overhead reduced by up to 85.1%

Achieved significant efficiency improvements with minimal storage increase

First study focusing on efficiency in blockchain supply chain traceability

Abstract

Supply chain traceability refers to product tracking from the source to customers, demanding transparency, authenticity, and high efficiency. In recent years, blockchain has been widely adopted in supply chain traceability to provide transparency and authenticity, while the efficiency issue is understudied. In practice, as the numerous product records accumulate, the time- and storage- efficiencies will decrease remarkably. To the best of our knowledge, this paper is the first work studying the efficiency issue in blockchain-based supply chain traceability. Compared to the traditional method, which searches the records stored in a single chunk sequentially, we replicate the records in multiple chunks and employ parallel search to boost the time efficiency. However, allocating the record searching primitives to the chunks with maximized parallelization ratio is challenging. To this end, we model the records and chunks as a bipartite graph and solve the allocation problem using a maximum matching algorithm. The experimental results indicate that the time overhead can be reduced by up to 85.1% with affordable storage overhead.