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Table Tennis Stroke Recognition Based on Body Sensor Network Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Distributed Genomic Compression in MapReduce Paradigm

Authors : Pasquale De Luca, Stefano Fiscale, Luca Landolfi, Annabella Di Mauro

Published in: Internet and Distributed Computing Systems

Publisher: Springer International Publishing

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Abstract

In recent years the biological data, represented for computational analysis, has increased in size terms. Despite the representation of the latter is demanded to specific file format, the analysis and managing overcame always more difficult due to high dimension of data. For these reasons, in recent years, a new computational framework, called Hadoop for manage and compute this data have been introduced. Hadoop is based on MapReduce paradigm to manage data in distributed systems. Despite the gain of performance obtained from this framework, our aim is to introduce a new compression method DSRC by decreasing the size of output file and make easy its processing from ad-hoc software. Performance analysis will show the reliability and efficiency achieved by our implementation.

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Metadata
Title
Distributed Genomic Compression in MapReduce Paradigm
Authors
Pasquale De Luca
Stefano Fiscale
Luca Landolfi
Annabella Di Mauro
Copyright Year
2019
Book
Internet and Distributed Computing Systems

Print ISBN: 978-3-030-34913-4

Electronic ISBN: 978-3-030-34914-1

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-34914-1_35

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