Characterizing Big Data Software Architectures: A Systematic Mapping Study

Autor(es)

Sena, Bruno ; Allian, Ana Paula ; Nakagawa, Elisa Yumi ; ACM

• Tipo de documento: Artigo Científico
• Fonte: XI BRAZILIAN SYMPOSIUM ON SOFTWARE COMPONENTS, ARCHITECTURES, AND REUSE (SBCARS 2017); v. N/A, p. 10-pg., 2017-01-01.

Resumo

Big data is a broad term for large, dynamic, and complex data sets that have brought great challenges to be addressed by traditional software systems. It has also demanded advanced software architectures (i.e., the big data software architectures) prepared to deal with the continuous expansion of the volume of data as well as to take advantage of new technologies for big data context. However, the main characteristics, basic requirements, and modules and organization of big data architectures are not still widely known. Besides that, no detailed overview about them is available. The main contribution of this paper is to present the state of the art related to big data software architectures; for this, we conducted a Systematic Mapping Study. As results, an essential set of eight requirements for big data architectures was identified, besides a collection of five modules that are fundamental to adequately enable the data flow. We also intend these results can guide architects in the development of software systems for this new challenging scenario of big data management. (AU)

• Processo FAPESP: 16/15634-3 - Uma abordagem para extração de conhecimento de SoS no contexto de Big Data
• Beneficiário: Bruno Sena da Silva
• Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
• Processo FAPESP: 14/02244-7 - SASoS: projeto arquitetural de sistemas de sistemas intensivos em software
• Beneficiário: Elisa Yumi Nakagawa
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/06195-9 - RASoS: construção de arquiteturas de referência de sistemas-de-sistemas
• Beneficiário: Elisa Yumi Nakagawa
• Modalidade de apoio: Auxílio à Pesquisa - Regular