2011/06/29 by Alexandru Costan, Florin Pop, Costan, Alexandru +10
Computer Science · Decision Sciences · #Advanced Data Storage Technologies #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Parallel #Scientific Computing and Data Management #Simulation Techniques and Applications #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1106.5846
17th International Conference on Control Systems and Computer Science (CSCS 17), Bucharest, Romania, May 26-29, 2009. Vol. 1, pp. 407-414, ISSN: 2066-4451
arxiv created 2011/06/29 · openalex publication_date 2011/06/29 · arxiv updated 2011/06/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With recent increasing computational and data requirements of scientific applications, the use of large clustered systems as well as distributed resources is inevitable. Although executing large applications in these environments brings increased performance, the automation of the process becomes more and more challenging. While the use of complex workflow management systems has been a viable solution for this automation process in business oriented environments, the open source engines available for scientific applications lack some functionalities or are too difficult to use for non-specialists. In this work we propose an architectural model for a grid based workflow management platform providing features like an intuitive way to describe workflows, efficient data handling mechanisms and flexible fault tolerance support. Our integrated solution introduces a workflow engine component based on ActiveBPEL extended with additional functionalities and a scheduling component providing efficient mapping between tasks and available resources.