Netinfo Security ›› 2017, Vol. 17 ›› Issue (7): 11-17.doi: 10.3969/j.issn.1671-1122.2017.07.002

• Orginal Article • Previous Articles     Next Articles

A YARN-based Smart Grid Big Data Abnormal Detection

Yang CHEN1(), Yong WANG2, Wei SUN3   

  1. 1. Center of Modern Education Technology, Anhui Polytechnic University, Wuhu Anhui 241000, China
    2. School of Computer and Information, Anhui Polytechnic University, Wuhu Anhui 241000, China
    3. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 610054, China
  • Received:2017-05-12 Online:2017-07-20 Published:2020-05-12

Abstract:

The defects of processing smart grid big data in Map-Reduce early version were also discussed, and the advantages of processing smart grid big data in YARN were also described in this paper. The coding model and implementation and advantages of YARN-DPP were also analyzed. In order to demonstrate the effectiveness of YARN-DPP, the hardware configuration environments and software running environments had been completed. A serial of simulation experiments in IEEE 118 node grid system were also done. The results and performance analysis demonstrated that good throughput and speedup had been obtained in YARN-DPP. It can meet the fast demands in large scale grid system big data processing. The computing speed was faster than sequence computation and Map-Reduce computation.

Key words: smart grid, big data, YARN normalization, Map-Reduce

CLC Number: