Blockchain Based Salmon Cold Chain Multi-chain Collaborative Supervision Model

In the context of the cluster development in the cold chain industry, the challenge of cross-chain signature data transmission and slow verification efficiency caused by the continuity and fragmentation of regulatory data in the collaborative process of salmon cold chain management was addressed. To tackle this issue, a blockchain-based multi-chain collaborative regulatory model for salmon cold chain management was proposed. The model incorporated a data verification and cold chain pattern monitoring method based on the aggregate signature algorithm, which ensured both the authenticity and integrity of salmon cold chain management while enhancing the efficiency of cross-chain regulatory data verification. Furthermore, a prototype system of the multi-chain collaborative regulatory model for salmon cold chain management on the Ethereum platform was implemented. Performance testing of the system revealed that the multi-chain architecture showed an average improvement of 17. 98% in regulatory performance compared with the single-chain architecture, with the advantage becoming more pronounced as the number of blockchain transactions were increased. In terms of verification efficiency, the slope analysis of the verification time curve indicated that the aggregate signature algorithm had a significant advantage with a slope of 0. 553, as opposed to the traditional verification algorithm with a slope of 57.448. This demonstrated that the aggregate signature algorithm exhibited remarkable efficiency advantages as the number of signatures were increased. Regarding communication overhead, the traditional signature algorithm required a maximum signature communication of up to 4 875 B under theoretical limits, while the aggregate signature algorithm consistently maintained a signature communication of 96 B, even without compression. The test results showed that the aggregate signature and verification method exhibited significant efficiency advantages in the batch data transmission and verification of the salmon cold chain scenario, providing valuable insights and references for trustworthy cold chain management and the development of cluster-based cold chains. © 2024 Chinese Society of Agricultural Machinery. All rights reserved.