Frank van Lingen

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Clarens is a Grid-enabled web service infrastructure implemented to augment the current batch-oriented Grid services computing model in the Compound Muon Solenoid (CMS) experiment of the LHC. Clarens servers leverage the Apache web server to provided a scalable framework for clients to communicate with services using the SOAP and XML-RPC protocols. This(More)
Monte Carlo production in CMS has received a major boost in performance and scale since the past CHEP06 conference. The production system has been re-engineered in order to incorporate the experience gained in running the previous system and to integrate production with the new CMS event data model, data management system and data processing framework. The(More)
Grid computing aims to provide an infrastructure for distributed problem solving in dynamic virtual organizations. It is gaining interest among many scientific disciplines as well as the industrial community. However, current grid solutions still require highly trained programmers with expertise in networking, high-performance computing, and operating(More)
Large scientific collaborations are moving towards service oriented architectures for implementation and deployment of globally distributed systems. Clarens is a high performance, easy to deploy Web service framework that supports the construction of such globally distributed systems. This paper discusses some of the core functionality of Clarens that the(More)
The Grid Analysis Environment (GAE), which is a continuation of the CAIGEE project [5], is an effort to develop, integrate and deploy a system for distributed analysis. The current focus within the GAE is on the CMS experiment [1] however the GAE design abstracts from any specific scientific experiment and focuses on scientific analysis in general. The GAE(More)
High energy physics (HEP) and other scientific communities have adopted service oriented architectures (SOA) as part of a larger grid computing effort. This effort involves the integration of many legacy applications and programming libraries into a SOA framework. The grid analysis environment (GAE) (Lingen et al., 2004) is such a service oriented(More)
Selecting optimal resources for submitting jobs on a computational grid or accessing data from a data grid is one of the most important tasks of any grid middleware. Most modern grid software today satisfies this responsibility and gives a best-effort performance to solve this problem. Almost all decisions regarding scheduling and data access are made by(More)