A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is
developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host
wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The
roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to
sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing
center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for
measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the
bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly
from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless
sensor networks.
The paper presents an analysis of technology trends based on the data available from the recently released National Technology Roadmap for Semiconductors (NTRS 1997). This analysis shows that increasing clock rates and system diameter in clock periods will make efficient management of communication and coordination increasingly critical. Due to the decreasing cost of logic versus interconnect and the electrical necessity of signal regeneration to counter worsening effect of interconnect geometries, use of configurable logic blocks even in custom data-paths presents a unique opportunity to customize bindings, mechanisms, and policies which comprise the interaction of processing, memory, I/O and communication resources. This programming flexibility, or `customizability,' can provide the key to achieving robust high performance. We use the results of this study to make a case for evolution of computer architectures into `Application Adaptive' (AA) architectures. These architectures exploit the capability of the underlying hardware to reconfigure logic to achieve system-level cost/performance goals by extensive analysis and profiling of application data and runtime characteristics. A key distinction made by AA architectures against traditional custom-computing machines is that architectural flexibility is used to customize architectural mechanisms and policies (instead of building additional functional resources--an approach commonly adopted by custom computing machines). Thus relatively small amounts of reconfigurable circuit blocks can be leveraged to yield high performance on a per application basis.
We present methods for architectural adaptation that use application-specific hardware assists and policies to provide substantial improvements in performance on a per application basis. We have used architectural customization to improve performance of the memory hierarchy and utilize network bisection for the multiprocessor architecture. We demonstrate the utility of architectural customization in efficient memory hierarchy management and memory bandwidth requirements using an application in sparse matrix manipulations. The experimental work is presented in the context of the MORPH machine that is currently being designed to provide high system performance by directly addressing memory system limitations in the current machines. Based on our preliminary results, we propose that an application-driven machine customization provides a cost effective way to achieve high performance and combat performance fragility while maintaining application retargetability across architectures.
Fabrication- and measurement-induced stresses in surface micromachined structures are investigated by wafer-level probing of electrostatically actuated polysilicon test structures fabricated by the MUMPs process of MCNC. The test structures are based on M-Test, an electrostatic pull-in approach for monitoring process uniformity and reproducibility, and, when used in conjunction with suitable geometric data, for measuring material properties. The sensitivity of the pull-in technique reveals that the simple step of placing the die on a vacuum probe station can significantly affect the measured results. The presence of strain gradients in the polysilicon and compliant structural supports for the beams makes the modeling more complex than for ideal geometries, but with appropriate adjustments to the models, and with knowledge of the strain gradient obtained from cantilever tip deflection as a function of beam length, the technique enables a measurement of the elastic modulus and the fabrication-induced residual stress.
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