A Performance Modeling Language For Big Data Architectures

Enrico Barbierato, Marco Gribaudo, Mauro Iacono

Risultato della ricerca: Contributo in libroContributo a convegno

22 Citazioni (Scopus)

Abstract

Big Data applications represent an emerging field, which have proved to be crucial in business intelligence and inmassive data management. Big Data promises to be the next big thing in the development of strategical computer applications, even if it requires considerable investment and an accurate resource planning, as the architectures needed to perform at the requisite speed need to scale easily on to a large number of computing nodes. Appropriate management of such architectures benefits from the availability of performance models, to allow developers and administrators to take informed decisions, saving time and experimental work. This paper presents a dedicated modeling language showing firstly how it is possible to ease the modeling process and secondly how the semantic gap between modeling logic and the domain can be reduced.
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings, 27th European Conference on Modelling and Simulation, ECMS 2013
Pagine511-517
Numero di pagine7
DOI
Stato di pubblicazionePubblicato - 2013
Evento27th EUROPEAN CONFERENCE ON MODELLING AND SIMULATION - Ålesund, Norway
Durata: 27 mag 201330 mag 2013

Workshop

Workshop27th EUROPEAN CONFERENCE ON MODELLING AND SIMULATION
CittàÅlesund, Norway
Periodo27/5/1330/5/13

Keywords

  • Big Data
  • metamodeling
  • modeling tools
  • performance modeling

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