CAREER: Design Optimization and Quantitative Evaluation of Wireless Embedded Sensing Systems

无线嵌入式传感系统（WESS）在推动研究和教育活动的同时，也使许多学科的创新成为可能。不幸的是，由于缺乏普遍接受的指标和基准套件，以及再现传感条件的困难，即使是今天的专家也无法轻松比较竞争的WESS设计。PI为wess的定量评估确定了基于健康的指标。为了最大限度地适应不同的传感要求，包括尺寸、功率和时序，PI构建了一个模块化、可配置的多微控制器WESS架构，称为微型集群，涵盖了从超紧凑、无线网络事件探测器到高占空比数据采集单元的各个领域。微集群的真正并行性增强了时间适应度，而分散、多电源、负载匹配的电源管理技术最大化了电源适应度并提高了数据适应度。如此优化的嵌入式系统将通过平衡能量收集和消耗，同时及时提供高质量的数据，从而达到新的能源效率水平。为了实现WESS基准测试，PI扩展了b#电池模拟器，以模拟具有完全再现性的环境刺激和非理想电源。为了基于实际应用中具体的、可测量的结果来推进WESS领域，PI组装并发布了一个全面的、真实世界的基准套件、基于仿真的评估框架和WESS架构，并向整个研究社区开放。PI通过与土木和机械工程、医学和表演艺术领域的合作者的实际部署来评估WESS架构，同时在这些领域推进最先进的技术。引人注目的应用程序驱动程序使项目课程对学生有益，并为特别是针对妇女和少数民族的外展活动增添了兴奋。

Wireless embedded sensing systems (WESS) are enabling innovations in many disciplines while driving research and education activities. Unfortunately, even experts today cannot easily compare competing WESS designs due to the lack of commonly accepted metrics and benchmark suites, and difficulties with reproducing sensing conditions. The PI identifies fitness-based metrics for quantitative evaluation of WESSs. To maximize fitness to the diverse sensing requirements, including size, power, and timing, the PI constructs a modular, configurable, multi-microcontroller WESS architecture called pico-cluster that spans the space from ultra-compact, wirelessly-networked event detectors to high duty-cycle data acquisition units. True parallelism of a pico-cluster enhances timing fitness, while de-centralized, multi-supply, load-matching power management techniques maximize power fitness and improve data fitness. Embedded systems so optimized will achieve new levels of energy efficiency by balancing energy harvesting and consumption while delivering high-quality data in a timely manner. To enable WESS benchmarking, the PI extends the B# battery emulator to emulating environmental stimuli and non-ideal power sources with full reproducibility. To advance the field of WESS based on concrete, measurable results from actual applications, the PI assembles and distributes a comprehensive, real-world benchmark suite, emulation-based evaluation framework, and the WESS architecture openly to the research community at large. The PI evaluates WESS architectures by actual deployment with collaborators in civil and mechanical engineering, medicine, and performance art while advancing the state-of-the-art in these fields. The compelling application drivers make project courses rewarding for students and add excitement to outreach activities particularly for women and minorities.