The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications
Keywords:Computing and Data Grids, distributed computing, distributed science applications
AbstractGrid technology has evolved over the past several years to provide the services and infrastructure needed for building ``virtual'' systems and organizations. With this Grid based infrastructure that provides for using and managing widely distributed computing and data resources in the science environment, there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects, institutions, and countries. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large-scale science projects located at multiple laboratories and universities. We also present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of Grid based services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources, such as databases, data catalogues, and archives; and collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science requirements in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios, both large and small scale, as well as various commercial and cultural cyberinfrastructure applications.
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How to Cite
Johnston, W. E. (2012). The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications. COMPUTING AND INFORMATICS, 21(4), 293–319. Retrieved from https://www.cai.sk/ojs/index.php/cai/article/view/485