Extending the SOA paradigm to e-Science environments

Service oriented architecture for scientific analysis at W7-X. An example of a field line tracer

“…In scientific applications large datasets are usually generated and transfered in a service call [8]. For example, the tracer can accept a magnetic field array from an equilibrium solver or a large machine model.…”

“…Arrays can either be stored externally [8], in a proxy or in a database, or can be represented in a binary form [24,25]. In the former case the datasets are labeled with a unique identifier, which also helps to unload the central node [8,49].…”

“…Still another option for using web-services is to employ the industry workflow standard BPEL [30], which brings off the shelf software like GUI designers and run-time engines, but has shortcomings concerning dynamic resource, long runs and large data packages [8].…”

“…The idea of using web-services for scientific computing emerged a few years ago [4] and has been widely adopted [5,6,7,8]. In fusion, SOAP web-services were proposed earlier: for Bayesian data analysis [9], for distributed applications [10], for W7-X data access [11], as a W7-X analysis framework [12].…”

An SOA-Based Model for the Integrated Provisioning of Cloud and Grid Resources

“…In particular, the works in [4,5] have shown the advantages and the feasibility, but also the problems, of modeling e-Science environments and infrastructures according to the serviceoriented architecture (SOA) and its enabling technologies such as web services (WS). Among the main advantages of such approach, we find interoperability, open standards, modularity, dynamic publish-find-bind, and programmatic access.…”