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Abstract
Many e-science applications take already advantage of numerous e-science infrastructures that evolved differently over the last couple of years. Along with this evolution, we observe still slow adoption of the open grid services architecture (OGSA) concept and thus interoperability between these infrastructures is still not seamlessly provided today. We argue that this is due to the absence of a realistically implementable reference model in Grids. In this contribution, we present our approach as one element of this reference model that focuses on the missing link between two emerging standards in the field of job management and information models in order to facilitate common open standards-based Grid interoperability.
During the past decade, significant international and broader interdisciplinary research is increasingly carried out by global collaborations that often share resources within a single production e-science infrastructure. More recently, increasing complexity of e-science applications embrace multiple physical models (i.e. multi-physics) and consider longer and more detailed simulation runs as well as a larger range of scales (i.e. multi-scale). This increase in complexity is creating a steadily growing demand for cross-infrastructure operations that take the advantage of multiple e-science infrastructures with a more variety of resource types. Since interoperable e-science infrastructures are still not seamlessly provided today we proposed in earlier work the Infrastructure Interoperability Reference Model (IIRM) that represents a trimmed down version of the Open Grid Service Architecture (OGSA) in terms of functionality and complexity, while on the other hand being more specifically useful for production and thus easier to implement. This contribution focuses on several important reference model invariants that are often neglected when infrastructure integration activities are being performed thus hindering seamless interoperability in many aspects. In order to indicate the relevance of our invariant definitions, we provide insights into two accompanying cross-infrastructure use cases of the bio-informatics and fusion science domain.
This document specifies the semantics and structure of the Job Submission Description Language (JSDL). JSDL is used to describe the requirements of computational jobs for submission to
resources, particularly in Grid environments, though not restricted to the latter. The document
includes the normative XML Schema for the JSDL, along with examples of JSDL documents
based on this schema.
In the last couple of years, many e-Science infrastructures have begun to offer production services to e-Scientists with an increasing number of applications that require access to different kinds of computational resources. Within Europe two rather different multi-national e-Science infrastructures evolved over time namely Distributed European Infrastructure for Supercomputing Applications (DEISA) and Enabling Grids for E-SciencE (EGEE). DEISA provides access to massively parallel systems such as supercomputers that are well suited for scientific applications that require many interactions between their typically high numbers of CPUs. EGEE on the other hand provides access to a world-wide Grid of university clusters and PC pools that are well suited for farming applications that require less or even no interactions between the distributed CPUs. While DEISA uses the HPC-driven Grid technology UNICORE, EGEE is based on the gLite Grid middleware optimized for farming jobs. Both have less adoption of open standards and therefore both systems are technically non-interoperable, which means that no e-Scientist can easily leverage the DEISA and EGEE infrastructure with one suitable client environment for scientific applications. This paper argues that future interoperability of such large e-Science infrastructures is required to improve e-Science in general and to increase the real scientific impact of world-wide Grids in particular. We discuss the interoperability achieved by the OMII-Europe project that fundamentally improved the interoperability between UNICORE and gLite by using open standards. We also outline one specific scientific scenario of the WISDOM initiative that actually benefits from the recently established interoperability.
Simulation and thus scientific computing is the third pillar alongside theory and experiment in todays science and engineering. The term e-science evolved as a new research field that focuses on collaboration in key areas of science using next generation infrastructures to extend the powers of scientific computing. This paper contributes to the field of e-science as a study of how scientists actually work within currently existing Grid and e-science infrastructures. Alongside numerous different scientific applications, we identified several common approaches with similar characteristics in different domains. These approaches are described together with a classification on how to perform e-science in next generation infrastructures. The paper is thus a survey paper which provides an overview of the e-science research domain.