Towards reliable, performant workflows for streaming-applications on cloud platforms

Daniel Zinn, Quinn Hart, Timothy McPhillips, Bertram Ludäscher, Yogesh Simmhan, Michail Giakkoupis, Viktor K. Prasanna

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Scientific workflows are commonplace in eScience applications. Yet, the lack of integrated support for data models, including streaming data, structured collections and files, is limiting the ability of workflows to support emerging applications in energy informatics that are stream oriented. This is compounded by the absence of Cloud data services that support reliable and performant streams. In this paper, we propose and present a scientific workflow framework that supports streams as first-class data, and is optimized for performant and reliable execution across desktop and Cloud platforms. The workflow framework features and its empirical evaluation on a private Eucalyptus cloud are presented.

Original languageEnglish (US)
Title of host publicationProceedings - 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2011
Pages235-244
Number of pages10
DOIs
StatePublished - Aug 10 2011
Externally publishedYes
Event11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2011 - Newport Beach, CA, United States
Duration: May 23 2011May 26 2011

Publication series

NameProceedings - 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2011

Other

Other11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2011
CountryUnited States
CityNewport Beach, CA
Period5/23/115/26/11

Keywords

  • abstraction
  • clouds
  • fault tolerance
  • reliability
  • scientific workflows
  • streaming

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

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