3 Mullica Jaroensutasine Krisanadej Jaroensutasinee Tony Fountain Michael Nekrasov Sirilak Chumkiew Premrudee Noonsang Uthai Kuhapong Scott Bainbridge. 2011 Submitted to Environmental Information Management 3 Robert Herlien, Tom O’Reilly, Kent Headley, Duane R. Edgington, Sameer Tilak, Tony Fountain, Peter Shin 2010 IEEE Sensors Hawaii IEEE 01/11/2010 We describe our implementation of a novel deep ocean sensor network, the MBARI Free Ocean CO2 Enrichment (FOCE). FOCE is a system designed for installation in the deep ocean to enable manipulative experiments that explore the impact of deep ocean increase in CO2 and resulting pH change on ocean biogeochemistry and ecology. This system uses control feedback and pH sensors to inject CO2 into a small volume of seawater, thus creating a controlled environment per science requirements. To implement this system, we utilized the MBARI-developed network middleware known as â��SIAMâ��, which provides a standardized interface to instruments on a sensor network. For the FOCE application we integrated Open Source DataTurbine (OSDT) into SIAM. OSDT provides asynchronous communication links between distributed components, and is particularly well-suited to streaming instrument data. Combined with the existing synchronous SIAM framework, these features enabled a straightforward and efficient architecture for our application. We describe how we achieved our goals of software reuse of infrastructure and instrument services, instrument-in-the-loop control, and rapid assembly of a scalable end-to-end sensor network system. 31 Tom O'Reilly, Kent Headley, Bob Herlien, Karen A Salamy, Sameer Tilak, Duane Edgington, Tony Fountain, Peter Brewer, Bill Kirkwood 2010 IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS) 2010 3 Tony Fountain Sameer Tilak Peter Shin Sally Holbrook Russell J. Schmitt Andrew Brooks Libe Washburn David Salazar 2009 Fifth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) 07/12/2009 Digital Moorea is a collaborative vision of a coral reef ecosystem instrumented with real-time sensors connected to high-performance backend resources and sophisticated client applications. It will be a living laboratory for long-term studies of marine ecology and a testbed for evolving technologies for environmental and biological sensing, communications, and analysis. A diverse team of ecologists, computer scientists, and engineers from the Marine Science Institute at the University of California Santa Barbara (MSI, www.msi.ucsb.edu/) and the California Institute of Telecommunications and Information Technology (CalIT2, www.calit2.net/) are collaborating to bring this vision to reality at the Moorea Coral Reef site (MCR LTER, www.mcr.lternet.edu) of the U.S. National Science Foundationâ��s Long Term Ecological Research (LTER) program. 3 Tony Fountain Sameer Tilak Paul Hubbard Peter Shin Lawrence Freudinger 2009 International Symposium on Remote Sensing of Environment The Open Source DataTurbine Initiative is an international community of scientists and engineers sharing a common interest in real-time streaming data middleware and applications. The technology base of the OSDT Initiative is the DataTurbine open source middleware. Key applications of DataTurbine include coral reef monitoring, lake monitoring and limnology, biodiversity and animal tracking, structural health monitoring and earthquake engineering, airborne environmental monitoring, and environmental sustainability. DataTurbine software emerged as a commercial product in the 1990â��s from collaborations between NASA and private industry. In October 2007, a grant from the USA National Science Foundation (NSF) Office of Cyberinfrastructure allowed us to transition DataTurbine from a proprietary software product into an open source software initiative. This paper describes the DataTurbine software and highlights key applications in environmental monitoring. 31 Peter Shin 2009 An integrated cyberinfrastructure for real-time data acquisition and decision making in smart buildings On March 4th 2009, Triton Engineering Student Council (TESC) in UCSD Jacobs School of Engineering hosted a dinner with deans for the first time. During the "green engineering" themed dinner, the deans of the engineering school encouraged multidisciplinary collaborations among students and faculties. As a computer science graduate student, I presented a short overview of a "smart building" project with Professor Jan Kleissl and Professor Paul Linden from Mechanical and Aerospace Engineering (MAE) department. The attached slides briefly explains how we are integrating DT with Esper to automate building control operations in real time. 31 Paul Hubbard 2008 DataTurbine presentation at PASI Costa Rica 31 Tony Fountain, Sameer Tilak 2008 Jane Rutherford and delegation from Canada Open Source DataTurbine Initiative: Streaming Data Middleware and Applications A quick overview of Open Source DataTurbine Initiative. 31 Paul Hubbard, Larry Miller 2008 3 Sameer Tilak Peter Arzberger David Balsiger Barbara Benson Rohit Bhalerao Kenneth Chiu Tony Fountain David Hamilton Paul Hanson Tim Kratz Fang-Pang Lin Tim Meinke Luke Winslow 2007 The third International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) 2007 Melbourne, Australia 12/03/2007 Freshwater lakes provide a number of important ecosystem services such as supply of drinking water, support of biotic diversity, transportation of commercial goods, and opportunity for recreation. Wireless sensor networks allow continuous, fine-grained, in situ measurements of key variables such as water temperature, dissolved gases, pH, conductivity, and chlorophyll. Instrumenting lakes with sensors capable of sampling environmental variables is becoming a standard practice. Furthermore, many limnologists around the world are interested in getting access to and performing research on data collected from lakes around the globe to provide local, regional and even global understanding of lake ecosystems. To that end, a number of limnologists, information technology experts, and engineers have joined forces to create a new, grassroots, international network, the Global Lake Ecological Observatory Network. One of our goals is to build a global scalable, persistent network of lake ecology observatories. However, implementing and designing technology that meets requirements of a large-scale distributed observing systems such as GLEON has, thus far, been challenging and instructive. In this paper, we describe several key conceptual challenges in building GLEON network. We also describe several practical issues and lessons learned during operation of a typical GLEON site. 3 Ebbe Strandell Sameer Tilak Hsiu-Mei Chou, Yao-Tsung Wang Fang-Pang Lin Peter Arzberger Tony Fountain 2007 The third International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) 2007 Melbourne, Australia 12/03/2007 The management of real-time streaming data in large-scale collaborative applications presents major processing, communication and administrative challenges. To that end, an open-source RBNB DataTurbine provides an excellent basis for developing robust streaming data middleware. The current RBNB DataTurbine streaming data middleware system satisfies a core set of critical infrastructure requirements including reliable data transport, the promotion of sensors and sensor streams to first-class objects, a framework for the integration of heterogeneous instruments, and a comprehensive suite of services for data management, routing, synchronization, monitoring, and visualization. As a part of PRAGMA telescience group, in collaboration with the National Center for High-Performance Computing (NCHC) Taiwan, researchers at the San Diego Supercomputer Center (SDSC) deployed RBNB DataTurbine-based system to acquire data from underwater cameras (in the ocean) at Kenting. More specifically, we describe a system that integrates sensors (underwater video cameras) with computing and storage Grids to create a complete fabric for conducting e-Science. The system is currently used for observation by marine research scientists at the Biodiversity Research Center of Academia Sinica in Taiwan. The described system increased performance and availability of the captured videos and we are, so far, pleased with its results. 3 Kaustubh Kulkarni Sameer Tilak Kenneth Chiu, Tony Fountain 2007 The third International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) 2007 Melbourne, Australia 12/03/2007 Wireless sensor networks can be embedded within complex environments for a wide range of monitoring and control applications including study of fire spread in woods, contamination spread in water bodies, or diffusion of toxic gases through air. In these applications, the collected data is used to drive a forecasting model, typically consisting of a CFD simulation. Traditionally, the data collection process is fixed. Active coupling between the sensor and the model, however, can significantly improve the accuracy, timeliness, and efficiency of forecasting. While there has been significant work in this area, there has not yet been a systematic analysis of how to represent the complex environments, how to represent the model, and how to architect the system. In this paper, we present a generalization of data-coupling applications, and describe a framework for decomposing models, which we apply to a simple example of water contamination. 3 Paul Hubbard 2007 11/10/07 30-minute SDSC booth talk on DataTurbine, SDCI and current coolness. Heavy on pictures. 31 Paul Hubbard 2007 None HPWREN User Group Meeting San Diego, CA None 2007 11/06/2007 3 Sameer Tilak Paul Hubbard Matt Miller Tony Fountain 2007 e-Science Bangalore, India 10/12/2007 The environmental science and engineering communities are actively engaged in planning and developing the next generation of large-scale sensor-based observing systems. These systems face two significant challenges: heterogeneity of instrumentation and complexity of data stream processing. Environmental observing systems incorporate instruments across the spectrum of complexity, from temperature sensors to Acoustic Doppler Current Profilers, to streaming video cameras. Managing these instruments and their data streams is a serious challenge. Critical infrastructure requirements common to all of these sensor-based observing systems are reliable data transport, the promotion of sensors and sensor streams to first-class objects, a framework for the integration of heterogeneous instruments, and a comprehensive suite of services for data management, routing, synchronization, monitoring, and visualization. In this paper we present the RBNB DataTurbine, an open-source streaming data middleware system, and discuss how the RBNB DataTurbine satisfies the critical cyberinfrastructure requirements core to these sensor-based observing systems. The discussion includes the results from real-world deployments. 31 Paul Hubbard 2007 Scripps Technical Forum Technical 60-minute talk for STF, heavy on details with very complex demonstrations. Tutorial, demo w/detailed instructions. http://stf.ucsd.edu/ 3 Corneliu Cotofana Longjiang Ding Peter Shin Sameer Tilak Tony Fountain Jennifer Eakins Frank Vernon 2006 IEEE International Conference on Web Services (ICWS) 9/18/2006 Large-scale observing systems are poised to become the dominant means of study for a variety of natural phenomena. These systems are comprised of hundreds to thousands of instruments that must be queried, managed, and shared in a scalable fashion. Services-oriented architectures (SOAs) are widely recognized as the preferred framework for building scalable and extensible cyberinfrastructure. By applying SOA concepts, we created a framework for organizing observing system resources. Guided by this framework, we developed web services, custom workflow applications, and an integrated user interface of monitors and controls for managing instruments in large-scale sensor network observing systems. In this paper we present our approach and discuss its application to the NSF EarthScope USArray large-scale seismic observing system.