Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/15546
Title: Optimizing Hadoop Performance for Big Data Analytics in Smart Grid
Authors: Khan, M
Huang, Z
Li, M
Taylor, GA
Ashton, PM
Khan, M
Keywords: Science & Technology;Technology;Physical Sciences;Engineering, Multidisciplinary;Mathematics, Interdisciplinary Applications;Engineering;Mathematics;MAPREDUCE;DESIGN
Issue Date: 2017
Publisher: HINDAWI LTD
Citation: MATHEMATICAL PROBLEMS IN ENGINEERING, (2017)
Abstract: 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 fromPMUs. To that extent the Hadoop framework, an open source implementation of theMapReduce 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 theHadoop 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.
URI: http://bura.brunel.ac.uk/handle/2438/15546
DOI: http://dx.doi.org/10.1155/2017/2198262
ISSN: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000415607100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=f12c8c83318cf2733e615e54d9ed7ad5
ARTN 2198262
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000415607100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=f12c8c83318cf2733e615e54d9ed7ad5
ARTN 2198262
1024-123X
1563-5147
Appears in Collections:Publications

Files in This Item:
File Description SizeFormat 
Mathematical Problems in Engineering - MK.pdf2.37 MBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.