804
Complete Tolerance Relation based Filling Algorithm using Spark
Jingling Yuan, Yao Xiang, Xian Zhong, Mincheng Chen and Tao Li
Wuhan University of Technology, Wuhan University of Technology, Wuhan University of Technology, Wuhan University of Technology, University of Florida

With the advent of cloud computing, renewable energy is integrated into data center power supply systems increasingly. The power statistics collection may not be available due to the instability of renewable energy, which results in incomplete data. The incomplete energy data will significantly disturb the management of data centers. We further propose a filling algorithm based on complete tolerance class. The algorithm expands the traditional tolerance relation, and fills the missing values of the energy data, which ensures the data integrity. By taking good advantage of in-Memory Computing, We further parallelize and optimize our algorithm using Spark. The experiment results demonstrate that our algorithm outperforms other general filling algorithms in terms of filling accuracy. The proposed algorithm also shows good performance as the missing rate rises up.