Research on Optimization Strategy for Data Clustered Storage Using a Consistent Hash Algorithm

We present a consistent Hash data-optimized multiple-copy distributed clustered storage placement strategy using technology to determine the storage location and rack selection to ensure a balanced distribution of data storage. The new strategy is able to complete the expansion according to the actual requirement of the clusters, and to complete the development of adaptive optimization based on the expansion, thus accelerating the speed of data processing. Experiments show that the execution speed has been effectively improved, ensuring the load balance. Extensions and reducing problems are situations possible to occur in real circumstances. The new strategy is utilized and tested in these situations. The results show that the oscillation has little impact on the load balancing, and the execution time is consistent with the proportion of the load trends as well.