Lambda Station is an ongoing project of Fermi National Accelerator Laboratory and the California Institute of Technology. The goal of this project is to design, develop and deploy network services for path selection, admission control and flow based forwarding of traffic among data- intensive Grid applications such as are used in High Energy Physics and other communities. Lambda Station deals with the last-mile problem in local area networks, connecting production clusters through a rich array of wide area networks. Selective forwarding of traffic is controlled dynamically at the demand of applications. This paper introduces the motivation of this project, design principles and current status. Integration of Lambda Station client API with the essential Grid middleware such as the dCache/SRM Storage Resource Manager is also described. Finally, the results of applying Lambda Station services to development and production clusters at Fermilab and Caltech over, advanced networks such as DOE's UltraScience Net and NSF's UltraLight is covered.

In this paper we present the motivation, the design, and a recent demonstration of the UltraLight testbed at SC|05. The goal of the Ultralight testbed is to help meet the data-intensive computing challenges of the next generation of particle physics experiments with a comprehensive, network- focused approach. UltraLight adopts a new approach to networking: instead of treating it traditionally, as a static, unchanging and unmanaged set of inter-computer links, we are developing and using it as a dynamic, configurable, and closely monitored resource that is managed from end-to-end. To achieve its goal we are constructing a next-generation global system that is able to meet the data processing, distribution, access and analysis needs of the particle physics community. In this paper we will first present early results in the various working areas of the project. We then describe our experiences of the network architecture, kernel setup, application tuning and configuration used during the bandwidth challenge event at SC|05. During this Challenge, we achieved a record-breaking aggregate data rate in excess of 150 Gbps while moving physics datasets between many Grid computing sites.

In this paper we present the design and implementation of the mission-oriented USLHCNet for HEP research community and the UltraLight network testbed. The design philosophy for these networks is to help meet the data-intensive computing challenges of the next generation of particle physics experiments with a comprehensive, network-focused approach. Instead of treating the network as a static, unchanging and unmanaged set of intercomputer links, we are developing and using it as a dynamic, configurable, and closely monitored resource that is managed from end-to-end. In this paper we will present our work in the various areas of the project including infrastructure construction, protocol research and application development. Our goal is to construct a next-generation global system that is able to meet the data processing, distribution, access and analysis needs of the particle physics community.

The latest WAN infrastructure and Grid-based Web Services will be used to demonstrate movement and analysis of TeraByte-scale event datasets for particle physics. Optimized transfers of data over 10Gbit/sec networks linking servers and disk systems will be shown using the latest processors, PCI-Express NICs, RAID arrays and firmware. All available lambdas arriving at the SC06 show floor will be saturated, in full duplex mode. The WAN performance will be monitored using the MonALISA distributed agent-based system. A suite of Grid-enabled Analysis tools developed at Caltech, University of Florida and Michigan will be used, as will. EGEE, OSG, ATLAS and CMS data management software such as SRM, dCache, FTS, and PhEdEx. Prototypes of the latest version of parallel NFS will demonstrate excellent utilization of 10Gbit/sec connections during execution of the analysis tasks.We intend to exceed the aggregate rate of 150Gbits/sec we achieved in our SC2005 Bandwidth Challenge winning entry.

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 architecture based on the Clarens grid services framework (Steenberg et al., 2004) and is being developed as part of the compact muon solenoid (CMS) experiment at the large hadron collider (LHC) at European Laboratory for Particle Physics (CERN). Clarens provides a set of authorization, access control, and discovery services, as well as XMLRPC and SOAP access to all deployed services. Two implementations of the Clarens Web services framework (Python and Java) offer integration possibilities for a wide range of programming languages. This paper describes the Java implementation of the Clarens Web services framework called 'JClarens' and several Web services of interest to the scientific and grid community that have been deployed using JClarens.

In this paper we describe JClarens; a Java based implementation of the Clarens remote data server. JClarens provides Web services for an interactive analysis environment to dynamically access and analyze the tremendous amount of data scattered across various locations. Additionally this research is aimed to develop a service oriented grid enabled portal (GEP) that provides interface and access to several grid services to give a homogeneous and optimized view of the distributed and heterogeneous environment. Other than showing platform independent behavior provided by Java, the use of XML-RPC based Web services enabled JClarens to be a language neutral server and demonstrated interoperability with its Python variant. Extreme care has been taken in the usage and manipulation of various Java libraries to cater the needs of high performance computing. The overall exercise has yielded in a prototype with strong emphasis on security and virtual organization management (VOM). This shall provide a common platform to support development of larger, more flexible framework with future aims to integrate it with a loosely coupled, decentralized, and autonomous framework for grid enabled analysis environment (GAE).