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2018 IEEE 11th International Conference on Cloud Computing (CLOUD) (2018)
San Francisco, CA, USA
Jul 2, 2018 to Jul 7, 2018
ISSN: 2159-6190
ISBN: 978-1-5386-7235-8
pp: 879-882
ABSTRACT
Many streaming frameworks have been introduced to deal with the needs for online analysis of massive datasets. Scientific applications often require significant changes to make them compatible with these frameworks. Other issues include tight coupling with the underlying infrastructure, shared computing environment, static topology settings, and complex configuration. In this article we present HarmonicIO, a lightweight streaming framework specialized for scientific datasets. It boasts a smart dynamic architecture, is highly elastic, and enforces a clear separation between framework components and application execution environment using container technology.
INDEX TERMS
Engines, Containers, Peer-to-peer computing, Streaming media, Throughput, Sockets
CITATION

P. Torruangwatthana, H. Wieslander, B. Blamey, A. Hellander and S. Toor, "HarmonicIO: Scalable Data Stream Processing for Scientific Datasets," 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), San Francisco, CA, USA, 2018, pp. 879-882.
doi:10.1109/CLOUD.2018.00126
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