Efficient processing and classification of wave energy spectrum data with a distributed pipeline

Gankevich I.G., Degtyarev A.B.
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Processing of large amounts of data often consists of several steps, e.g. pre- and post-processing stages, which are executed sequentially with data written to disk after each step, however, when pre-processing stage for each task is different the more efficient way of processing data is to construct a pipeline which streams data from one stage to another. In a more general case some processing stages can be factored into several parallel subordinate stages thus forming a distributed pipeline where each stage can have multiple inputs and multiple outputs. Such processing pattern emerges in a problem of classification of wave energy spectra based on analytic approximations which can extract different wave systems and their parameters (e.g. wave system type, mean wave direction) from spectrum. Distributed pipeline approach achieves good performance compared to conventional “sequential-stage” processing.

Keywords: distributed system, big data, data processing, parallel computing
Citation in English: Gankevich I.G., Degtyarev A.B. Efficient processing and classification of wave energy spectrum data with a distributed pipeline // Computer Research and Modeling, 2015, vol. 7, no. 3, pp. 517-520
Citation in English: Gankevich I.G., Degtyarev A.B. Efficient processing and classification of wave energy spectrum data with a distributed pipeline // Computer Research and Modeling, 2015, vol. 7, no. 3, pp. 517-520
DOI: 10.20537/2076-7633-2015-7-3-517-520
URL: http://crm-en.ics.org.ru/journal/article/2301/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.
According to Crossref, this article is cited by:
  • Ivan Gankevich, Yuri Tipikin, Vladimir Korkhov, Vladimir Gaiduchok, Alexander Degtyarev, Alexander Bogdanov. Computational Science and Its Applications – ICCSA 2016. / Lecture Notes in Computer Science. — 2016. — V. 9787. — P. 379. DOI: 10.1007/978-3-319-42108-7_29
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