To optimize the parallel clustering scheduling effect of distributed storage big data, this study proposes the design of a decision tree based parallel clustering scheduling algorithm for distributed storage big data. This method first constructs a decision tree model to achieve distributed storage data classification, and then implements parallel design of the decision tree model based on the Storm platform to improve data classification speed. Finally, based on this, a distributed storage data clustering scheduling design is implemented using an improved BPSO algorithm. The experimental results show that the proposed method has a shorter scheduling time and is superior to traditional methods, with better application results.

Pan Jinfeng, Hu Xiaoqin. Distributed Storage Big Data Parallel Clustering Scheduling Algorithm Based on Decision Tree. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 13: 9-13. https://doi.org/10.25236/AJCIS.2023.061302.

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