2019 Vol.2 Dec. No.6

• Title: Clustering Migration Algorithm for Redundant Information in Hybrid Cloud Storage Based on Big Data
• Name: Stuart Rauber
• Company: Memorial University of Newfoundland
• Abstract:

  The traditional method tends to fall into local convergence during the data clustering process, which leads to a decrease in the accuracy of the clustering. To this end, a clustering migration algorithm based on big data redundant information in hybrid cloud storage is proposed. Based on the principle analysis of cloud storage big data clustering, based on the traditional fuzzy C-means clustering, redundant data clustering migration algorithm is adopted to implement the reform design of big data clustering algorithm. Based on the construction of cloud storage system structure model and fuzzy B-means clustering algorithm description, the redundant information cluster migration algorithm is improved and designed. Perform hybrid clustering design on big data in cloud storage systems to reduce storage overhead and improve data management and scheduling capabilities.

• Keyword: Big Data; Cloud Storage; Clustering; Hybrid;
• DOI: 10.12250/jpciams2019060643
• Citation form: Stuart Rauber.Clustering Migration Algorithm for Redundant Information in Hybrid Cloud Storage Based on Big Data[J]. Computer Informatization and Mechanical System, 2019, vol. 2, pp. 157-162.

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