Discontinuity, Nonlinearity, and Complexity
Nonlinear Time Series Analysis of Complex Systems Using an e-Science Web Framewor
Discontinuity, Nonlinearity, and Complexity 7(2) (2018) 129--141 | DOI:10.5890/DNC.2018.06.002
Bruno B. F. Leonor; Walter A. dos Santos; Asiel Bomfin Jr.; Reinaldo R. Rosa
National Institute for Space Research, São José dos Campos, Brazil
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Abstract
The analysis of time series in the era of Big Data has become a major challenge for computational framework research. Furthemore, in the areas of space science which deals with a large variety of data, the practical consistence between workload, workflow and cloud computing is crucial. Here, such consistence is provided by an innovative e-Science framework project named Sentinel which is based on a NoSQL data base (MongoDB) and a containerization platform (Docker). This web framework supports researchers for time series analysis in a cloud environment where they can easily access, parameterize, initialize and monitor their applications. As a case study in the Brazilian Space Weather Program, we consider the intensive analysis of time series from a complex information system for solar activity monitoring and forecasting. As a prototype for implementing the framework, the DFA (detrended fluctuation analysis) technique was used as a nonlinear spectrum analyzer applied to the solar irradiance measurements from 1978 to 2012. Moreover, new applications can be added and managed by researchers on the portal easily to complement their data analysis purposes.
Acknowledgments
The authors would like to thank Vanessa C. Oliveira de Souza for providing the DFA code used in the case study presented. The authors are greatful to the PMOD/WRC, Davos, Switzerland for the dataset provided (composite d41 62 1204.txt) from the VIRGO Experiment on the cooperative ESA/NASA Mission SOHO. RRR acknowledge financial support from FAPESP through the grant No 2014/11156.
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