Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 509981
Title Software metrics for green parallel computing of big data systems
Author(s) Gurbuz, Havva Gulay; Tekinerdogan, Bedir
Source In: Proceedings - 2016 IEEE International Congress on Big Data, BigData Congress 2016. - Institute of Electrical and Electronics Engineers Inc. - ISBN 9781509026227 - p. 345 - 348.
Event 5th IEEE International Congress on Big Data, BigData Congress 2016, San Francisco, 2016-06-27/2016-07-02
DOI http://dx.doi.org/10.1109/BigDataCongress.2016.54
Department(s) Information Technology
WASS
Publication type Contribution in proceedings
Publication year 2016
Keyword(s) Big data - Green computing - Metrics - Parallel computing component
Abstract

Big Data is typically organized around a distributed file system on top of which the parallel algorithms can be executed for realizing the Big Data analytics. In general, the parallel algorithms can be mapped in different alternative ways to the computing platform. Hereby each alternative will perform differently with respect to the environmentally relevant parameters such as energy and power consumption. Existing studies on deployment of parallel computing algorithms have mainly focused on addressing general computing metrics such as speedup with respect to serial computing and efficiency of the use of the computing nodes. In this paper, we report on the elicitation of green metrics for big data systems that are required when analyzing deployment alternatives. To this end we use the existing systematic literature reviews and identify, and discuss the important green computing metrics for big data systems.

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