Abstract
College physical education in China is facing a new reform in the context of informationization, and informatization is the focus of this reform. The physical health data mining of college students was studied in the paper from the perspective of cloud data. Firstly, the unified scheduling of students’ physique health data resources under cloud environment was analyzed. Secondly, in-depth research was conducted on the Yam system. And a new type of data mining and scheduling model Luna Scheduler was designed based on DRF algorithm. This model optimized Yam Capacity Scheduler in terms of scheduling algorithm, fine-grained resources classification, etc. Finally, the algorithm and model were tested, and the parameter configuration that could improve the throughput of Yam was given.
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Funding
Funding was provided by Anhui Provincial-level University Leading talent introduction and cultivation project (Grant No. gxyqZD2016008), Anhui Tourism Young expert cultivation project (Grant No. AHLYZJ201517), Research on Anhui Auto-Camping Industry Boosting System and its development Mode (Grant of Anhui Sports bureau) (Grant No. ASS2015309) and Study on the cultivation mode of Innovative college talents on experiential education (Grant No. 2015jyxm170).
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Xue, B., Liu, T. Physical Health Data Mining of College Students Based on DRF Algorithm. Wireless Pers Commun 102, 3791–3801 (2018). https://doi.org/10.1007/s11277-018-5410-5
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DOI: https://doi.org/10.1007/s11277-018-5410-5