A Brief of Distributed Data Processing
Keywords:
mapping study, data processing, distributed processing systemsAbstract
Distributed data processing is a cornerstone in modern cloud and edge computing environments because of its ability to handle large amounts of information that can overwhelm a single computer. However, the ontogeny of research in the field of distributed data processing remains poorly characterized. Therefore, we reviewed 70 publications discussing distributed data processing. Distributed processing systems is an active area of research with publications increasing in numbers since the early 2000s. The most salient topics in distributed processing systems were affiliated with system architecture and programming paradigms. However, researchers lack standard metrics for reporting throughput, hampering the comparison of existing studies. This study is a first step towards characterizing this field of research and identifying important areas of opportunity.
References
Akoka J., Comyn-Wattiau I., and Laoufi N. Research on big data–a systematic mapping study. Comp. Stand & Interfaces, 54:105–115, 2017.
Fahed Alkhabbas, Romina Spalazzese, and Paul Davidsson. Characteriz- ing internet of things systems through taxonomies: A systematic mapping study. Internet of Things, 7:100084, 2019.
Sean Bleier. Natural language took kit’s list of english stopwords. https://gist.github.com/sebleier/554280, 2021. Accessed: 2021-01-24.
D. Budgen, M. Turner, P. Brereton, and B. A. Kitchenham. Using mapping studies in soft. engineering. In PPIG, V8, pg. 195–204, 2008.
Omri M.N., Helali L. A survey of data center consolidation in cloud computing systems. doi.org/10.1016/j.cosrev.2021.100366, Feb 2021.
Machine Learning Group University of WAIKATO. Weka 3 - data mining with open source machine learning software in java. https://www.cs.waikato.ac.nz/ml/weka/, 2021. Accessed: 2021-01-24.
Thies W., and Amarasinghe S. An empirical characterization of stream programs and its implications for language and compiler design. In 2010 19th Int. Conf. on Parallel Architectures and Compilation Techniques (PACT), pages 365–376. IEEE, 2010.
Twitter. Decahose api. https://developer.twitter.com/en/docs/twitter- api/enterprise/decahose-api/overview/decahose, 2021.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Clemente Izurieta, Nate Woods, Ann Marie Reinhold
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
License Terms:
Except where otherwise noted, content on this website is lincesed under a Creative Commons Attribution Non-Commercial License (CC BY NC)
Use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes, is permitted.
Copyright to any article published by WiPiEC retained by the author(s). Authors grant WiPiEC Journal a license to publish the article and identify itself as the original publisher. Authors also grant any third party the right to use the article freely as long as it is not used for commercial purposes and its original authors, citation details, and publisher are identified, in accordance with CC BY NC license. Fore more information on license terms, click here.