Clustering Optimization Algorithm for Blockchain Systems Based on Big Data Analysis

【Author】 Lu, Yanjing

【Source】IETE JOURNAL OF RESEARCH

【影响因子】1.877

【Abstract】The clustering optimization is the need of the hour for the blockchain systems where the distributed data are generated in large volumes and mining of data is mandatory for analyzing the data. The poor clustering may lead to increase in outliers, poor analysis of data and instability in data. It may also slow down the data processing phase if clustering is not performed in a controlled and systematic manner. Therefore, this has motivated us to perform this research study. The objective of the study is to design a clustering optimization algorithm for blockchain systems based on big data analytics. A large number of related variables in the blockchain system are transformed into a small set of uncorrelated variables to remove noise and redundancy. The complex data dimensionality reduction is also performed. On this basis, K-means clustering algorithm is used for comparison and also to randomly select a centroid and then our proposed algorithm is adopted to cluster the data generated by blockchain system after dimensionality reduction, and the initial clustering center is obtained to collect similar data. At the same time, the self-identification intersection is used. The weighted K-means clustering algorithm is used initially to calculate the cluster center and then the heuristic algorithm is used for clustering of aligned data which realizes the clustering optimization of the blockchain-based generated data. The proposed clustering optimization has good clustering effect, greater stability, and fast convergence speed and is not affected by outliers as per the results obtained.

【Keywords】Big data analysis; bloakchain systems; clustering algorithm; optimization design

【发表时间】

【收录时间】2022-03-08

【文献类型】期刊

【主题类别】

区块链技术-区块链数据分析-