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Recent Developments on Security and Reliability in Large-Scale Data Processing with MapReduce

Esposito, Christian ; Ficco, Massimo

International journal of data warehousing and mining, 2016-01, Vol.12 (1), p.49-68 [Periódico revisado por pares]

Hershey: IGI Global

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  • Título:
    Recent Developments on Security and Reliability in Large-Scale Data Processing with MapReduce
  • Autor: Esposito, Christian ; Ficco, Massimo
  • Assuntos: Big Data ; Commerce ; Computer information security ; Computer networks ; Computer security ; Context ; Data mining ; Data processing ; Data security ; Distributed computing ; Distributed processing ; Information management ; Massive data points ; Mathematical models ; Methods ; Parallel processing ; Programming ; Reliability ; Security
  • É parte de: International journal of data warehousing and mining, 2016-01, Vol.12 (1), p.49-68
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: The demand to access to a large volume of data, distributed across hundreds or thousands of machines, has opened new opportunities in commerce, science, and computing applications. MapReduce is a paradigm that offers a programming model and an associated implementation for processing massive datasets in a parallel fashion, by using non-dedicated distributed computing hardware. It has been successfully adopted in several academic and industrial projects for Big Data Analytics. However, since such analytics is increasingly demanded within the context of mission-critical applications, security and reliability in MapReduce frameworks are strongly required in order to manage sensible information, and to obtain the right answer at the right time. In this paper, the authors present the main implementation of the MapReduce programming paradigm, provided by Apache with the name of Hadoop. They illustrate the security and reliability concerns in the context of a large-scale data processing infrastructure. They review the available solutions, and their limitations to support security and reliability within the context MapReduce frameworks. The authors conclude by describing the undergoing evolution of such solutions, and the possible issues for improvements, which could be challenging research opportunities for academic researchers.
  • Editor: Hershey: IGI Global
  • Idioma: Inglês;Ndongo
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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