Proceedings of the 10th Workshop on Workflows in Support of Large-Scale Science
- Creators
- Montagnat, Johan
- Taylor, Ian
- Others:
- Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS) ; Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- School of Computer Sciences & Informatics [Cardiff] ; Cardiff University
Description
This year is special for the WORKS series as this corresponds to the tenth issue of this scientific event dedicated to scientific workflows. The call for papers attracted thirteen submissions from Europe, the USA, India and Mexico. After peer reviews by the program committee, nine of the papers were accepted, covering a variety of topics: workflows tasks scheduling, resources allocation for efficient execution, data flows management, languages, workflow adaptation, virtualization and provenance.Looking over the past years, the problem of workflow scheduling and resources allocation in distributed infrastructures has always been well represented in the WORKS workshop series, with lan increasing interest for cloud type of resources lately. Together with scalability issues, they have represented a fundamental research axis over a long period of time. Accompanying infrastructure virtualization, effort has also been recently invested in abstract workflow representations and dynamic execution processes allowing for reconfiguration depending on the evolving execution conditions or intermediate results found. Finally, it can be seen from this year program that data flow management is a topic with a renewed interest in the broader context of scientific Big Data analysis.
Abstract
International audience
Additional details
- URL
- https://hal.science/hal-01338383
- URN
- urn:oai:HAL:hal-01338383v1
- Origin repository
- UNICA