CSR:Small: Energy Harvesting for Performance Sensitive Wireless Sensor Networks

该项目解决了传感器系统中的能源问题。能量收集允许无线传感器网络（WSN）应用从环境中提取和存储能量。 某些不断发展的应用程序类别，特别是那些支持长期监控和监视系统等关键基础设施的应用程序类别，需要更高级别的通信和计算性能。通常，这类应用程序中的系统必须能够对不可预见的或紧急情况提供强大而灵活的响应。许多这些拟议中的应用还需要自主运行数年甚至数十年，因此可能需要能量收集技术。目前的基于无线传感器网络的能量收集方法通常不提供这类应用的协调的能量管理策略。该项目以三种方式解决这一差距。首先，该团队正在设计和评估一套最佳的能量收集策略，该策略将联合收割机动态电压缩放（改变CPU速度）与动态调制缩放（改变无线传输速率）相结合。这些算法有效地支持具有广泛工作负载的时间关键型应用程序，同时保持必要的能量储备以应对紧急情况。其次，是分布式协议的发展，以实现这些算法。 最后，是两个能量采集硬件测试平台，基于流动的水能源发电系统和基于太阳能的能量采集器在混合机器人传感器网络应用的原型的开发。这两个原型测试平台不仅将产生关键的技术见解，而且将向不同背景的学生介绍网络，设备和机器人设计的问题。PI有一个多步骤的计划，以整合他们的研究和教育使命的建议。这包括开发新课程，扩大和加强学校在能源管理方面的努力，通过STEM计划为高中教师开发为期一周的训练营，并为GMU机器人和传感器实验室的发展做出贡献。

This project addresses energy issues in sensor systems. Energy harvesting permits wireless sensor network (WSN) applications to extract and store energy from the environment. Certain evolving application classes, particularly those supporting critical infrastructures like long-term monitoring and surveillance systems, require higher levels of communication and computational performance. Often, systems in this application class must be able to provide robust and flexible responses to unforeseen or emergency situations. Many of these proposed applications will also be required to run autonomously for years or even decades, and therefore may require energy harvesting techniques. Current methods for WSN-based energy harvesting typically do not provide a coordinated energy management policy for this class of applications. This project addresses this gap in three ways. First, the team is designing and evaluating a set of optimal energy harvesting policies that combine dynamic voltage scaling (changing the CPU speed) with dynamic modulation scaling (changing wireless transmission rates.) The algorithms efficiently support time-critical applications that have a wide range of workloads while maintaining necessary energy reserves in order to deal with emergency situations. Second, is the development of distributed protocols to implement these algorithms. Finally, is the development of prototypes of two energy harvesting hardware testbeds, a flow-based water energy generation system and a solar-based energy harvester used in a hybrid robotic sensor network application. The two prototype testbeds will not only yield critical technical insight but will introduce students of various backgrounds into the issues of networking, device, and robotic design. The PIs have a multi-step plan to integrate their research and education mission of their proposal. This includes development of new courses, expanding and strengthening the schools effort on energy management, developing week-long training camps for high school instructors through the STEM program, and contributing to the advancement of the GMU robotics and sensor labs.