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In response to the problems of the practical Byzantine fault-tolerant algorithm (PBFT), such as random selection of master nodes and poor scalability, a CART-based PBFT optimization algorithm is proposed, namely the C-PBFT algorithm. First, the introduction of weighted impurity variables improves the CART algorithm, overcomes the mutual influence of attributes between nodes, and improves the classification accuracy. Secondly, through the point grouping mechanism, the nodes are divided into three types: consensus nodes, candidate nodes, and alternate nodes, which are dynamically adjusted based on node behavior to ensure the reliability of consensus nodes. Finally, the voting weight is introduced into the consensus node, and the consensus is reached by using the voting weight exceeding the threshold, which reduces the message transmission in the blockchain network and improves the efficiency of the algorithm operation. The experimental results show that the improved consensus algorithm has better performance in terms of delay, throughput, and fault tolerance and reduces the frequent switching of views caused by the failure of the master node.

This thesis shows the importance of considering technologies such as blockchain to identify an information improvement process in a supply chain problem. We propose an extension of the paper ”Economics of Permissioned Blockchain Adoption” (Iyengar et al. 2020) where the number of consumers is discrete. This extension provides comparative statics of the consumer’s and manufacturer’s welfare under the adoption or non-adoption of the technology. We confirm the results of the original paper regarding the challenges of successful adoption, but with specific results respecting the importance of the size of the market (number of consumers) and the distribution of manufacturers among low and high- quality types. Furthermore, we show the advantages that this technology can offer through the Practical Byzantine Fault Tolerance consensus (PBFT) that guarantees the correctness of the information. Finally, using a two-sided markets model we provide a preliminary setup of a fee system that creates incentives to enter the platform: the blockchain network. Our results suggest that implementing blockchain improves the consumer’s welfare, while the manufacturer’s welfare varies depending on the quality of the product they offer in the market. In addition, we analyze a consensus mechanism to reduce information asymmetries and the restructuring of the problem as a model of two-sided markets. This thesis shows the importance of considering technologies such as blockchain to identify an information improvement process in a supply chain problem. We propose an extension of the paper ”Economics of Permissioned Blockchain Adoption” (Iyengar et al. 2020) where the number of consumers is discrete. This extension provides comparative statics of the consumer’s and manufacturer’s welfare under the adoption or non-adoption of the technology. We confirm the results of the original paper regarding the challenges of successful adoption, but with specific results respecting the importance of the size of the market (number of consumers) and the distribution of manufacturers among low and high- quality types. Furthermore, we show the advantages that this technology can offer through the Practical Byzantine Fault Tolerance consensus (PBFT) that guarantees the correctness of the information. Finally, using a two-sided markets model we provide a preliminary setup of a fee system that creates incentives to enter the platform: the blockchain network. Our results suggest that implementing blockchain improves the consumer’s welfare, while the manufacturer’s welfare varies depending on the quality of the product they offer in the market. In addition, we analyze a consensus mechanism to reduce information asymmetries and the restructuring of the problem as a model of two-sided markets.

Aiming at the problems of centralized storage, low sharing efficiency, and the security and privacy of traditional medical data, a medical data storage model based on a consortium chain is proposed. First, the Distance algorithm is designed based on the geographical relationship of nodes, which reduces the amount of communication between nodes, improves the communication efficiency between A nodes, and ensures the efficiency and reliability of grouping. Second, the dynamic election is combined with the Distance algorithm to design the election strategy of the primary node, which realizes the scientific and reasonable ranking of the medical nodes, improves the reliability of the selection of the primary node, and ensures the efficiency of the medical nodes in the alliance chain to quickly reach consensus when the medical data are uploaded to the chain. Finally, the model designs a method of information separation, which combines the distributed database IPFS (InterPlanetary File System) with the blockchain, which greatly reduces the pressure of medical data storage in the blockchain and improves the operation efficiency. The experimental results show that the medical data storage model can effectively improve the problem of the sharp increase in the amount of communication between medical nodes in the network and reduce the impact of malicious consensus nodes.