Optimizing Hadoop Performance for Big Data Analytics in Smart Grid
Joint Authors
Khan, Mukhtaj
Huang, Zhengwen
Li, Maozhen
Taylor, Gareth A.
Ashton, Phillip M.
Khan, Mushtaq
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-19
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The rapid deployment of Phasor Measurement Units (PMUs) in power systems globally is leading to Big Data challenges.
New high performance computing techniques are now required to process an ever increasing volume of data from PMUs.
To that extent the Hadoop framework, an open source implementation of the MapReduce computing model, is gaining momentum for Big Data analytics in smart grid applications.
However, Hadoop has over 190 configuration parameters, which can have a significant impact on the performance of the Hadoop framework.
This paper presents an Enhanced Parallel Detrended Fluctuation Analysis (EPDFA) algorithm for scalable analytics on massive volumes of PMU data.
The novel EPDFA algorithm builds on an enhanced Hadoop platform whose configuration parameters are optimized by Gene Expression Programming.
Experimental results show that the EPDFA is 29 times faster than the sequential DFA in processing PMU data and 1.87 times faster than a parallel DFA, which utilizes the default Hadoop configuration settings.
American Psychological Association (APA)
Khan, Mukhtaj& Huang, Zhengwen& Li, Maozhen& Taylor, Gareth A.& Ashton, Phillip M.& Khan, Mushtaq. 2017. Optimizing Hadoop Performance for Big Data Analytics in Smart Grid. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1189792
Modern Language Association (MLA)
Khan, Mukhtaj…[et al.]. Optimizing Hadoop Performance for Big Data Analytics in Smart Grid. Mathematical Problems in Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1189792
American Medical Association (AMA)
Khan, Mukhtaj& Huang, Zhengwen& Li, Maozhen& Taylor, Gareth A.& Ashton, Phillip M.& Khan, Mushtaq. Optimizing Hadoop Performance for Big Data Analytics in Smart Grid. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1189792
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189792