Web网络大数据的聚类中心调度技术研究

Research on clustering center scheduling technology for Web network big data

针对传统调度方法一直存在调度精度不准确的问题,提出一种Web网络大数据的聚类中心调度技术的研究方案。针对Web网络大数据重新建立调度模型有效的对数据进行识别,优化聚类中心的K-means算法,解决对大数据调度能力差的问题,提高聚类中心的大数据调度能力,最后使用建立调度模型完成在Web网络大数据环境下的聚类中心数据调度。设计对比仿真试验,通过实验数据可以有效地证明Web网络大数据的聚类中心调度技术的有效性。

In allusion to the problem of the inaccurate scheduling precision of the traditional scheduling method, a research scheme of clustering center scheduiing technology for Web network big data is proposed. The Web network big data scheduling model is reconstructed for effective data recognition. The K-means algorithm in clustering center is optimized to resolve the prob- lem of poor big data scheduling capability and improve the big data scheduling capability in clustering center. The constructed scheduling model is employed to accomplish the data scheduling of clustering center in the Web network big data environment. The contrast simulation experiment was carried out. The experimental data effectively demonstrates the validity of the clustering center scheduling technology for Web network big data.