A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Distributed Computing Grid Experiences in CMS

The CMS experiment is currently developing a computing system capable of serving, processing and archiving the large number of events that will be generated when the CMS detector starts taking data. During 2004 CMS undertook a large scale data challenge to demonstrate the ability of the CMS computing system to cope with a sustained data-taking rate equivalent to 25% of startup rate. Its goals were: to run CMS event reconstruction at CERN for a sustained period at 25 Hz input rate; to distribute the data to several regional centers; and enable data access at those centers for analysis. Grid middleware was utilized to help complete all aspects of the challenge. To continue to provide scalable access from anywhere in the world to the data, CMS is developing a layer of software that uses Grid tools to gain access to data and resources, and that aims to provide physicists with a user friendly interface for submitting their analysis jobs. This paper describes the data challenge experience with Grid infrastructure and the current development of the CMS analysis system

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Condor services for the Global Grid:interoperability between Condor and OGSA

In order for existing grid middleware to remain viable it is important to investigate their potentialfor integration with emerging grid standards and architectural schemes. The Open Grid ServicesArchitecture (OGSA), developed by the Globus Alliance and based on standard XML-based webservices technology, was the first attempt to identify the architectural components required tomigrate towards standardized global grid service delivery. This paper presents an investigation intothe integration of Condor, a widely adopted and sophisticated high-throughput computing softwarepackage, and OGSA; with the aim of bringing Condor in line with advances in Grid computing andprovide the Grid community with a mature suite of high-throughput computing job and resourcemanagement services. This report identifies mappings between elements of the OGSA and Condorinfrastructures, potential areas of conflict, and defines a set of complementary architectural optionsby which individual Condor services can be exposed as OGSA Grid services, in order to achieve aseamless integration of Condor resources in a standardized grid environment