Executing multi-workflow simulations on a mixed grid/cloud infrastructure using the SHIWA and SCI-BUS technology

Peter Kacsuk, Gabor Terstyanszky, Akos Balasko, Krisztian Karoczkai, Zoltan Farkas

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)

Abstract

Large simulations require the combination of many different applications. In many cases they are described as scientific workflows. In the recent years significant knowledge accumulated in the form of scientific workflows. This helps scientists to build even more complex simulations particularly, if they combine existing simulations with new ones and create multi-workflow simulations. The SHIWA project created the SHIWA Simulation Platform to help scientist sharing and combining workflows to build such complex multi-workflow simulations that also require the use of as many computing resources as possible. The mixed use of grid and cloud infrastructure can provide the necessary amount of resources that are needed to complete complex multi-workflow simulations in reasonable time. The SCI-BUS project has created the gateway technology that enables the mixed use of grid and cloud infrastructures. The current paper describes the SHIWA and SCI-BUS technology and how they can be used to run multi-workflow simulations on the mixed grid and cloud infrastructures.

Original languageEnglish
Title of host publicationCloud Computing and Big Data
PublisherIOS Press BV
Pages141-160
Number of pages20
ISBN (Print)9781614993216
DOIs
Publication statusPublished - 2013

Publication series

NameAdvances in Parallel Computing
Volume23
ISSN (Print)0927-5452

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Keywords

  • Workflow
  • cloud computing
  • grid computing
  • simulation

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Kacsuk, P., Terstyanszky, G., Balasko, A., Karoczkai, K., & Farkas, Z. (2013). Executing multi-workflow simulations on a mixed grid/cloud infrastructure using the SHIWA and SCI-BUS technology. In Cloud Computing and Big Data (pp. 141-160). (Advances in Parallel Computing; Vol. 23). IOS Press BV. https://doi.org/10.3233/978-1-61499-322-3-141