Parallelization of Scientific Workflows in the Cloud

Abstract : Nowadays, more and more scientific experiments need to handle massive amounts of data. Their data processing consists of multiple computational steps and dependencies within them. A data-intensive scientific workflow is an appropriate tool for modeling such process. Since the execution of data-intensive scientific workflows requires large-scale computing and storage resources, a cloud environment, which provides virtually infinite resources is appealing. However, because of the general geographical distribution of scientific groups collaborating in the experiments, multisite management of data-intensive scientific workflows in the cloud is becoming an important problem. This paper presents a general study of the current state of the art of data-intensive scientific workflow execution in the cloud and corresponding multisite management techniques.
Complete list of metadatas
Contributor : Ji Liu <>
Submitted on : Tuesday, July 15, 2014 - 4:10:27 PM
Last modification on : Thursday, March 14, 2019 - 2:04:01 PM
Long-term archiving on : Monday, November 24, 2014 - 11:36:29 AM


Files produced by the author(s)


  • HAL Id : hal-01024101, version 1



Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso. Parallelization of Scientific Workflows in the Cloud. [Research Report] RR-8565, 2014. ⟨hal-01024101v1⟩



Record views


Files downloads