Big Data Movement: A Challenge in Data Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86097012" target="_blank" >RIV/61989100:27240/15:86097012 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985815:_____/15:00450861 RIV/00216208:11320/15:10282546 RIV/61989100:27740/15:86097012

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-11056-1_2" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-11056-1_2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-11056-1_2" target="_blank" >10.1007/978-3-319-11056-1_2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Big Data Movement: A Challenge in Data Processing

Popis výsledku v původním jazyce

This chapter discusses modern methods of data processing, namely its paralleliza-tion with attention to the bio-inspired methods. Explanation how selected evolu-tionary algorithms can do synthesis of novel methods are demonstrated on the astrophysical large data sets. Such approach is now characteristic for so called Big Data and Big Analytics. First, we describe some new database architectures sup-porting Big Data storage and processing. We discuss also Big Data problems, i.e. their sources, characteristics, processing, and analyzing. Parallelism in the service of data processing is introduced in detail. We show how new technologies force programmers to consider parallel processing not only in a distributive way (hori-zontal scaling), but also within each server (vertical scaling). The chapter also dis-cusses in large interdisciplinary intersection between astrophysics and computer science, i.e., so called astroinformatics with rich set of data sources and examples. The last part of the chapter is devoted to selected bio-inspired methods and their use on simple model synthesis from astrophysical Big Data collection. Some sug-gestion on how new algorithms can be synthesized by bio-inspired methods are mentioned as well as its possible use Big Data processing. We also give a brief overview on usability areas of the algorithms and end with some general remarks of the limits of computing.

Název v anglickém jazyce

Big Data Movement: A Challenge in Data Processing

Popis výsledku anglicky

This chapter discusses modern methods of data processing, namely its paralleliza-tion with attention to the bio-inspired methods. Explanation how selected evolu-tionary algorithms can do synthesis of novel methods are demonstrated on the astrophysical large data sets. Such approach is now characteristic for so called Big Data and Big Analytics. First, we describe some new database architectures sup-porting Big Data storage and processing. We discuss also Big Data problems, i.e. their sources, characteristics, processing, and analyzing. Parallelism in the service of data processing is introduced in detail. We show how new technologies force programmers to consider parallel processing not only in a distributive way (hori-zontal scaling), but also within each server (vertical scaling). The chapter also dis-cusses in large interdisciplinary intersection between astrophysics and computer science, i.e., so called astroinformatics with rich set of data sources and examples. The last part of the chapter is devoted to selected bio-inspired methods and their use on simple model synthesis from astrophysical Big Data collection. Some sug-gestion on how new algorithms can be synthesized by bio-inspired methods are mentioned as well as its possible use Big Data processing. We also give a brief overview on usability areas of the algorithms and end with some general remarks of the limits of computing.

Druh

C - Kapitola v odborné knize

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA13-08195S" target="_blank" >GA13-08195S: Vysoce škálovatelné paralelní a distribuované metody zpracování vědeckých dat</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Big Data in Complex Systems

ISBN

978-3-319-11055-4

Počet stran výsledku

41

Strana od-do

29-69

Počet stran knihy

500

Název nakladatele

Springer Verlag

Místo vydání

Heidelberg

Kód UT WoS kapitoly

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