A Reference Architecture for Blockchain-based Traceability Systems Using Domain-Driven Design and Microservices

TL;DR

This paper presents a reference architecture for blockchain-based traceability systems that leverages domain-driven design and microservices to enhance system maintainability, scalability, and performance in complex supply chain scenarios.

Contribution

It introduces a novel reference architecture for blockchain traceability systems using DDD and microservices, and proposes a multi-sub-chain approach to handle large data efficiently.

Findings

Improved system performance with multi-sub-chain networks.

Enhanced maintainability and extensibility of BTSs.

Effective prototype implementation in salmon supply chain.

Abstract

Traceability systems are important for solving problems due to the increasing scale of the global supply chain, such as food safety crises and market disorder. Blockchain, as an immutable and decentralized ledger, is able to optimize the traditional traceability system by ensuring the transparency and reliability of the system data. However, the use of blockchain technology may lead to a rapid increase in the complexity of system design and development. It is challenging to address widespread and complicated business, changeable processes, and massive data in practice, which are the main factors restricting the wide application of a blockchain-based traceability system (BTS). Therefore, in this paper, we reviewed relevant studies and proposed a reference architecture for BTSs. The proposed reference architecture can improve the cohesiveness, maintainability, and extensibility of BTSs through domain-driven design (DDD) and microservices. Considering the efficiency reduction caused by massive data and complicated data structure, we further changed the traditional single blockchain framework into multiple sub-chain networks, which could improve development efficiency and system performance. With the guidance of the architecture trade-off analysis method (ATAM), we evaluated our reference architecture and implemented a prototype in the salmon supply chain scenario. The results show that our solution is effective and adaptable to meet the requirements of BTSs.