College of Information Science and Technology, Shihezi University, Shihezi, China.
College of Information Science and Technology, Shihezi University, Shihezi, China.
Comput Biol Med. 2023 Mar;154:106590. doi: 10.1016/j.compbiomed.2023.106590. Epub 2023 Jan 29.
To solve the problems of high latency, high system overhead, and small supported scale in the current application of pharmaceutical traceability combined with blockchain technology, an algorithm called Pharmaceutical-Practical Byzantine Fault Tolerance (P-PBFT) based on PBFT, grouping, and credit voting is proposed. The algorithm combines the characteristics of a pharmaceutical supply chain, optimizes the consistency protocol in the original algorithm, divides large-scale network nodes into different consensus sets by response speed, and performs grouping consensus. The algorithm's credit model and voting mechanism dynamically updates user status according to the behavior of nodes in consensus, evaluates the reliability of users, and also serves as a basis for electing management nodes. Experimental results show that the improved P-PBFT consensus algorithm provides smaller latency and higher throughput for pharmaceutical traceability systems, supports larger-scale traceability, effectively alleviates the dramatic increase in communication among network nodes, and reduces the influence of malicious nodes.
为了解决当前医药追溯结合区块链技术应用中存在的高延迟、高系统开销和支持规模小的问题，提出了一种基于 PBFT、分组和信用投票的算法，称为医药实用拜占庭容错（P-PBFT）。该算法结合了医药供应链的特点，对原算法中的一致性协议进行了优化，根据响应速度将大规模网络节点划分为不同的共识集，并进行分组共识。算法的信用模型和投票机制根据共识中节点的行为动态更新用户状态，评估用户的可靠性，也作为选举管理节点的依据。实验结果表明，改进的 P-PBFT 共识算法为医药追溯系统提供了更小的延迟和更高的吞吐量，支持更大规模的追溯，有效缓解了网络节点间通信的急剧增加，降低了恶意节点的影响。
