Scalable Scientific Workflows Management System SWFMS

Abstract

Abstract-In today"s electronic world conducting scientific experiments, especially in natural sciences domain, has become more and more challenging for domain scientists since "science" today has turned out to be more complex due to the two dimensional intricacy; one: assorted as well as complex computational (analytical) applications and two: increasingly large volume as well as heterogeneity of scientific data products processed by these applications. Furthermore, the involvement of increasingly large number of scientific instruments such as sensors and machines makes the scientific data management even more challenging since the data generated from such type of instruments are highly complex. To reduce the amount of complexities in conducting scientific experiments as much as possible, an integrated framework that transparently implements the conceptual separation between both the dimensions is direly needed. In order to facilitate scientific experiments "workflow" technology has in recent years emerged in scientific disciplines like biology, bioinformatics, geology, environmental science, and eco-informatics. Much more research work has been done to develop the scientific workflow systems. However, our analysis over these existing systems shows that they lack a well-structured conceptual modeling methodology to deal with the two complex dimensions in a transparent manner. This paper presents a scientific workflow framework that properly addresses these two dimensional complexities in a proper manner.