The construction of blockchain platform for engineering museums based on vectorized image processing technology

Abstract

Abstract The characteristics of blockchain such as tamper-evident and distributed can effectively solve the increasingly prominent security and privacy issues in engineering pavilions, however, the current throughput of mainstream blockchain platforms is far from meeting the demand for rapid chain-up of massive data in engineering pavilions, and the high redundancy storage mechanism adopted by traditional blockchain cannot be applied to engineering pavilion scenarios. To address the above problems, based on vectorized image processing technology, a hierarchical blockchain architecture is first proposed to store block data in multiple distributed cloud servers and edge servers in a hierarchical manner to cope with the growing data volume in the industrial Internet. Then based on the topology between edge servers, a blockchain network slicing algorithm is designed based on an improved complex network association partitioning algorithm, which improves the blockchain network throughput while shortening the slicing time. Finally, the impact of block broadcast time on throughput is demonstrated by formalizing the block broadcast process as a spanning tree, based on which a spanning tree-based intra-slice master node selection algorithm is proposed to further improve the throughput of the blockchain network. The analysis and experimental results show that the proposed scheme effectively reduces the partitioning time of the blockchain network and the broadcast time of the blocks within each partition. Compared with the classical association partitioning algorithm, this paper's partitioning algorithm can reduce the partitioning time by about 36% without sacrificing the quality of partitioning when partitioning a large-scale network.