Collaborative Research: CSR-EHS: Obtaining Realistic Communication and Sensing In-situ Models for Wireless Embedded Systems

随着MEMS技术的不断进步，无线嵌入式系统被部署在从控制良好的实验室到湍急的海底的各种环境中。系统设计对由此产生的通信和感知模式做出了简单化、有时不切实际的假设。虽然嵌入式设备通常在部署前进行单独的微校准，但初步结果表明，部署环境是影响嵌入式设备通信和感知特性的主导因素。本研究旨在为现实环境下的大规模嵌入式系统开发广泛的建模方法和相关协议。该项目的主要目标在于开发三种新的建模方法，这三种方法相辅相成，涵盖了很大的成本效益设计空间。首先，基于不规则度和信令功率方差的概念，提出了一种新的无线电不规则性模型。第二个目标是使用自动捕获和回放流程来抽象完全可重复的物理环境。第三个特点是一种新的方式，以受控的方式使用训练事件来产生非参数的真实感知和通信模式。在资源受限的大规模嵌入式系统中构建和使用这些模型的一个关键挑战在于如何协调在线建模精度和相关成本之间的冲突。该项目旨在开发从微观到宏观的模型，其中设计师可以根据精度需求选择适当的细节级别，也可以从参数类型到非参数类型的模型，其中设计师可以根据可用的资源以适当的成本选择模型。这些模型将通过常见的仿真系统提供，使嵌入式系统设计人员能够基于真实感开发解决方案，并避免今天发现的通过仿真开发的解决方案在现实世界中不起作用的普遍问题。这反过来预计将对嵌入式系统产生重大影响，因为它节省了开发时间和资金，并导致更高效、更健壮、更可预测和更可控的系统。研究结果将使用明尼苏达大学和弗吉尼亚大学的交通监测和管理试验台进行评估。

With the continuing advancement of MEMS technology, wireless embedded systems are deployed in various kinds of environments from well-controlled laboratories to turbulent ocean floors. System design has made simplifying and sometimes unrealistic assumptions about the resulting communication and sensing patterns. Although embedded devices are normally micro-calibrated individually before deployment, preliminary results indicate that the deployment environment is a dominating factor in communication and sensing characteristics of embedded devices. This research aims at developing a wide spectrum of modeling methodologies and related protocols for large-scale embedded systems under realistic environments. The main objective of this project lies in developing three novel modeling approaches, which complement each other and cover a large cost-benefit design space. The first is to develop a new radio irregularity model based on concepts of degree of irregularity and variance of signaling power. The second seeks a capability for abstraction of a completely repeatable physical environment, using an automated capture-and-replay process. The third features a novel way to use training events in a controlled manner to produce non-parametric realistic sensing and communication patterns. A key challenge for in-situ modeling lies in reconciling the conflict between the in-situ modeling accuracy and the related cost to build and use these models in resource-limited large-scale embedded systems. This project seeks to develop the models from the micro to macro levels where designers can choose the appropriate level of detail based on the accuracy needs, and also the models from parametric to non-parametric types where designers can choose the models with proper costs based on the available resources. The models will be available via common simulation systems, enabling embedded systems designers to develop solutions based on realism and avoid an all-to-common problem found today where solutions developed by simulation don't work in the real world. This, in turn, is expected to have a major impact on embedded systems by saving development time and money and resulting in more efficient, robust, predictable and controllable systems. Research results will be evaluated using traffic-monitoring and management testbeds at the University of Minnesota and the University of Virginia.