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

该项目解决传感器系统中的能源问题。能量采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，此应用程序类中的系统必须能够对意外或紧急情况提供强大而灵活的响应。这些拟议中的许多应用程序还需要自主运行数年甚至数十年，因此可能需要能源收集技术。当前用于基于WSN的能量采集的方法通常不为这类应用提供协调的能量管理策略。该项目通过三种方式解决了这一差距。首先，该团队正在设计和评估一套最佳的能量收集策略，将动态电压调整(更改CPU速度)与动态调制调整(更改无线传输速率)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，以便处理紧急情况。第二，是开发分布式协议来实现这些算法。最后，开发了两个能量收集硬件试验台的原型，一个基于流动的水能发电系统，以及一个用于混合机器人传感器网络应用的基于太阳能的能量收集器。这两个原型试验台不仅将产生关键的技术洞察力，还将向不同背景的学生介绍网络、设备和机器人设计问题。私人投资机构有一个多步骤计划，将他们的研究和教育使命整合到他们的提案中。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计划为高中教师发展为期一周的训练营，并为推进GMU机器人和传感器实验室做出贡献。

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.