In this article, we examine the energy consumption of a set of sensors that transmit correlated information to a base station either directly or in an ad-hoc multihop fashion. Building on a single-hop distributed data rate allocation scheme, we present an efficient approximation algorithm for the NP-hard joint routing and data compression problem whose objective is to maximize the operation lifetime of the sensor networks. We prove that the performance of our algorithm lies within 1/O(log n) of the optimum value where n is the number of sensors. We use simulations to validate our intuitions and provide additional insights on the factors that impact the performance of the approximation scheme. The numerical results show that the proposed scheme performs close to the optimum.

In this paper we describe progress in the NSF-funded Ultralight project and a recent demonstration of Ultralight technologies at SuperComputing 2005 (SC|05). The goal of the Ultralight project 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. Thus 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 present the motivation for, and an overview of, the Ultralight project. We then cover early results in the various working areas of the project. The remainder of the paper describes our experiences of the Ultralight 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 sites interconnected by the Ultralight backbone network. The exercise highlighted the benefits of Ultralight's research and development efforts that are enabling new and advanced methods of distributed scientific data analysis.

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.

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.

The publication offers a note of thanks to its reviewers. Reviewers' comments are an essential part of the process of creating a well written article capable of expressing theoretical content well with effective illustrations, tables and graphs.

Looks at the UltraLight project which treats the network interconnecting globally distributed data sets as a dynamic, configurable, and closely monitored resource to construct a next-generation system that can meet the high-energy physics community's data-processing, distribution, access, and analysis needs.

In this paper, we study how to reduce energy consumption in large-scale sensor networks, which systematically sample a spatio-temporal field. We begin by formulating a distributed compression problem subject to aggregation (energy) costs to a single sink. We show that the optimal solution is greedy and based on ordering sensors according to their aggregation costs-typically related to proximity-and, perhaps surprisingly, it is independent of the distribution of data sources. Next, we consider a simplified hierarchical model for a sensor network including multiple sinks, compressors/aggregation nodes, and sensors. Using a reasonable metric for energy cost, we show that the optimal organization of devices is associated with a Johnson-Mehl tessellation induced by their locations. Drawing on techniques from stochastic geometry, we analyze the energy savings that optimal hierarchies provide relative to previously proposed organizations based on proximity, i.e., associated Voronoi tessellations. Our analysis and simulations show that an optimal organization of aggregation/compression can yield 8%-28% energy savings depending on the compression ratio.

High Energy Physics collaborations consist of hundreds to thousands of physicists and are world-wide in scope. Experiments and applications now running, or starting soon, need the data movement capabilities available now only on advanced and/or experimental networks. The Lambda Station project steers selectable traffic through site infrastructure and forwards it onto these "high- impact" wide-area networks. Lambda Station also controls ingress and egress filters between the site and the high-impact networks and takes responsibility for negotiating with reservation or provisioning systems that regulate the WAN control plane, be it based on SONET channels, demand tunnels, or dynamic optical links. This paper will discuss design principles, the current status of the project, the results achieved up to date, and challenges surmounted building Lambda Station aware applications using DOE's UltraScienceNet, ESnet UltraLight networks between Fermilab, Caltech, and other sites.