EHS: Real-Time Distributed Control Networks: Dynamic Bandwidth Allocation via Adaptive Sampling

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Ian A. Gravagne, Baylor University, Real-Time Distributed Networks: Dynamics Bandwidth Allocation via Adaptive Sampling This research applies an emerging field of mathematicsknown as Dynamic Equations on Time Scales to the problem of bandwidthutilization in real-time distributed control networks. Time scalestheory allows for the seamless analysis of dynamic processes oncontinuous, discrete, or mixed time domains, including non-uniformdiscrete time domains. Recent advances in time scales show that periodicservo control processes on distributed networks can adapt their timingcharacteristics in the presence of aperiodic high-priority trafficbursts without losing control of their plants. The adaptive servo timingmethod results in an increase in the effective available bandwidth foraperiodic traffic and better integration of the overallplant/processor/network system. Study of the theory of time scales isleading to further advances toward the unification of continuous anddiscrete systems as well. This unique applicationof an area of mathematics previously unknown to the computer science andengineering communities has the potential to stimulate externalresearch into related topics such as network scheduling and real-timecontrol performance.The project will pursue empirical validation of the new theory on a 40-nodeController Area Network of embedded processors developed at BaylorUniversity. Successful research in this area has immediateutility and potential economic impact for a large industrial baseemploying distributed control networks, notably in the automotive,aerospace, and manufacturing industries. Baylor'srelatively new graduate engineering programs will continue to supportthe educational needs of engineers employed by local industries in the underserved Central Texas area.