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

伊恩·A Gravagne，Baylor大学，实时分布式网络：通过自适应采样的动态带宽分配本研究应用了一个新兴的领域，称为时间尺度上的动态方程，以解决实时分布式控制网络中的带宽利用问题。时间尺度理论允许对连续、离散或混合时间域（包括非均匀离散时间域）上的动态过程进行无缝分析。时间尺度的最新进展表明，分布式网络上的伺服控制过程可以在不失去对工厂的控制的情况下，在存在非周期性高优先级流量突发的情况下调整其时序特性。自适应伺服定时方法导致非周期性流量的有效可用带宽的增加和整个工厂/处理器/网络系统的更好集成。时间尺度理论的研究也使连续系统和离散系统的统一有了进一步的发展。 这一独特的应用领域的数学以前未知的计算机科学和工程界有可能刺激外部研究到相关的主题，如网络调度和实时控制性能。该项目将追求实证验证的新理论上的40节点控制器区域网络的嵌入式处理器在贝勒大学开发。 在这一领域的成功研究具有直接的效用和潜在的经济影响的大型工业基地采用分布式控制网络，特别是在汽车，航空航天和制造业。 贝勒大学相对较新的研究生工程课程将继续支持德克萨斯州中部地区当地工业雇用的工程师的教育需求。

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.