CSR: Small: System and Network Support for Harvesting-aware Solar Sensor Networks

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。许多传感器网络部署在缺乏基础设施的恶劣地形中，但也需要使用太阳能收集来实现自我持续运行。太阳能采集感知传感器网络的设计提出了许多系统和网络挑战。从系统的角度来看，设计应该能够在广泛的能量收集场景动态范围下运行，从充足的阳光到非常有限的光线（例如，茂密的森林地区）。从网络的角度来看，协议栈应该能够适应由于树叶和日常变幻莫测的收获率的时空变化。在这个项目中，我们将为收获感知太阳能传感器网络设计系统和网络支持。我们的系统贡献包括新型传感器平台，该平台使用薄膜电池在弱光条件下进行采集，在高度可变的采集条件下进行预测性占空循环，以及轻量级检查点和重新启动以处理间歇性断电。我们的网络贡献包括一个针对占空比可变性进行优化的链路层，一个使用感知采集路径指标的网络层，以及一个可以在不同采集条件下提供高吞吐量的传输层。我们的教育计划包括通过暑期高中推广项目进行K-12教学，以及与哈佛森林大学合作的跨学科REU项目，为生态监测部署太阳能传感器网络。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Many sensor network deployments are in harsh terrain that lack infrastructure but also need to use solar energy harvesting for self-sustained operation. The design of harvesting-aware solar sensor networks raises numerous systems and networking challenges. From a systems perspective, a design should be able to operate under a wide dynamic range of energy harvesting scenarios, from plentiful sunlight to very limited light (e.g., thickly forested areas). From a network perspective, a protocol stack should be able to adapt to spatio-temporal variability in harvesting rates due to foliage and day-to-day vagaries.In this project, we will design systems and network support for harvesting-aware solar sensor networks. Our systems contributions include novel sensor platforms that use thin-film batteries for harvesting under low-light conditions, predictive duty-cycling under highly variable harvesting conditions, and lightweight checkpointing and restart to handle intermittent loss of power. Our networking contributions include a link layer that is optimized for duty-cycle variability, a network layer that uses harvesting-aware path metrics, and a transport layer can offer high throughput under diverse harvesting conditions.Our educational plans consist of K-12 teaching through a summer high school outreach program, and inter-disciplinary REU programs in collaboration with Harvard Forest for deploying solar-powered sensor networks for ecological monitoring.