Sensor Systems Technologies for Data-Driven Dynamic Scientific Applications

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CSR?CSI?SGER: Sensor Systems Technologies for Dynamic Data-Driven Scientific Applications The overall goal of this research project is to develop sensor system middleware and programming support that will enable distributed networks of sensors to function, not only as passive measurement devices, but as intelligent data processing instruments, capable of data quality assurance, statistical synthesis and hypotheses testing as they stream data from the physical environment to the computational world. Specifically, this exploratory project will address the following research components: investigate a programming system that will support the development of in-network data processing mechanisms, and will enable scientific/engineering applications to discover, query, interact with, and control instrumented physical systems using semantically meaningful abstractions; investigate services for active in-network data processing that will generate appropriate data/information to drive novel algorithms for modeling, interpretation and decision making, as well as algorithms for information acquisition with dynamic qualities and properties from streams of data from the physical environment, and explore how applications can control data acquisition; and investigate middleware services for the application-driven dynamic management of sensor systems for physical instrumentation, including overlay sensor system runtime management and adaptation, computation/communication/power tradeoffs and dynamic load-balancing. The proposed research activities will be performed driven and validated with two different applications: (1) subsurface modeling and geo-system management and control and (2) contaminant management and geo-system remediation. A key deliverable of this research will be an experimental infrastructure that will build on the NSF Orbit wireless sensor network testbed at Rutgers University and develop the software infrastructure that will enable scientists and engineers to experiment with different aspects of dynamic data-driven application systems (DDDAS), and will design this simulation environment in close collaboration with the 2 different application groups so that it closely emulates their DDDAS requirements.