2007-08 Program on Environmental Sensor Networks

Research Foci

• Sampling from Wireless Networks
• Environmental Modeling from Sensor Networks
• Sensor Networks, Forests and Global Change

• Planning Workshop, October 2007
• Kickoff Workshop and Tutorials, January 13-16, 2008
• Fall 2007 Course on Sensor Networks for Environmental Modeling
• Transition Workshop, October 20-21, 2008

• Sensor Networks Datasets
• Sensor Design

Introduction

Environmental sensor networks have the capability of capturing local and broadly-dispersed information simultaneously; they also have the capacity to respond to sudden change in one l ocation by triggering observations selectively across the network while simultaneously updating the underlying complex system model and/or reconfiguring the network. Data gathered by wireless sensor networks, either fixed or mobile, pose unique challenges for environmental modeling: a complex system is being observed by a dynamical network. Technical challenges in statistics (sampling design to prediction and prediction uncertainty), in mathematics (computational geometry to data fusion to robotics), and in computers science (self-organizing networks to algorithm analysis) combine with the technical challenges of the models themselves and the sciences that underlie them.

This program will bring together an interdisciplinary group of ecologists, mathematicians, statisticians, and computer scientists with the objective of formulating and addressing optimization of data gathering, data analysis, data coverage, modeling and inference when the network itself is a dynamic system of self-organizing nodes. This collaborative effort will include both development of new mathematical, computational and statistical tools and also specific application to existing environmental networks designed to study biosphere-atmospheric interactions.

Program Leaders: Zoe Cardon, Jorge Cortes, Don Estep, Debora Estrin, Paul Flikkema, Mark Hansen, Bin Yu (NAC Liaison); Jim Berger (Directorate Liaison); Jim Clark and Alan Gelfand (Local Scientific Coordinators)

Research Foci

Research foci will be built from themes involving 1) sampling: adaptive sampling and network-triggered observation, spatio-temporal sampling designs, 2) modeling: prediction and uncertainty, especially multiscale modeling, and 3) integral development of methodologies in the context of modeling forest response to global environmental change. Although the specific agendas for the research foci will be determined by the participants at the Opening Workshop, potential research topics might be drawn from the following questions.

Sampling from wireless networks:
Cost of spatio-temporal data in terms of both energy and delay: Each sample has a footprint in power in space and time, some value to one or more process models (e.g., importance of parameters in space and time, sensitivity of estimates to the observation), and some cost (e.g., data transmission). Is it possible to derive frameworks such that the utility of each sample exceeds its cost?

Frameworks for adaptive sampling: game-theoretic, reinforced learning, dynamic experimental design. How can a sampling scheme to respond to highly non-stationary dynamics in energy-constrained sampling networks. Are modes of operation controlled by adaptive state machines enough?

Environmental modeling from sensor networks:
Model complexity and adequacy: In the trade-off of dimensionality and predictive accuracy, what are the diagnostics for excessive vs. insufficient parametrization? Can models be developed so that reduced forms (e.g., deleting submodels, subsets of parameters, or reducing resolution of observations and/or parameter specification) still function simultaneously with near-optimality at several scales?

Prediction Uncertainty: Appropriate modeling of sources of uncertainty due to sampling (e.g., "lost" samples, outliers, bad sensors, measurement noise, and unreliable communication), and integration of data models with process models.

Model adequacy: Is there coherent noise in bio-micrometeorological systems that should drive exploration of new regions of the state space?

Networks, forests and global change:
Process level understanding of how forested ecosystems respond to global change is critical for anticipating consequences of human impacts on landscapes. To be successful an approach will entail integrated models of a complex system and will involve heterogeneous data and analyses that directly address uncertainty and model selection issues.

Specific analyses will focus on increasing the capacity to forecast consequences of global change, using existing data from forest sensor networks as both testbed and primary research objective.

Inference on scaling relationships will be implemented in simulation of whole forests to examine potential consequences of changing climate and atmospheric CO2 for forest diversity and carbon sequestration. These results will have immediate application to the problem of forecasting biosphere responses to atmospheric change.

Description of Activities

Workshops: A Planning Workshop in October and a preparatory graduate course will begin the program in Fall 2007. The principal goal of the workshop will be to engage a broadly representative segment of the applied mathematical, statistical, computational and environmental science communities to determine research directions to be pursued by working groups during the program.

The Kickoff Workshop will take place in January 2008 to examine existing networks, models and data, preparatory to integration of mathematical/computational/statistical aspects of sensor networks into the understanding of these specific forest networks and these specific environmental models for global change. There will also be mid-program workshops organized by the working groups, and a Transition Workshop during Summer 2008, to disseminate program results and chart a path for future research in the area.

Working Groups: The working groups meet regularly throughout the program to pursue particular research topics identified in the kickoff workshop (or subsequently chosen by the working group participants). The working groups consist of SAMSI visitors, postdoctoral fellows, graduate students, and local faculty and scientists. It is not necessary to be continually resident at SAMSI to maintain connection to the working groups.

Further Information

Additional information about the program and opportunities to participate in it is available:

• For research visits, including New Researcher Fellowships and SAMSI-University Fellowships, consult Visiting and Employment Opportunities for 2007-08.
• For postdoctoral appointments, consult Postdoctoral Positions for 2007-08.
• For other questions, send E-mail to [email protected].

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