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Grafting Energy-Harvesting Leaves onto the Sensornet Tree

机译:将收集能量的叶子移植到Sensornet树上

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We study the problem of augmenting battery-powered sensornet trees with energy-harvesting leaf nodes. Our results show that leaf nodes that are smaller in size than today's typical battery-powered sensors can harvest enough energy from ambient sources to acquire and transmit sensor readings every minute, even under poor lighting conditions. However, achieving this functionality, especially as leaf nodes scale in size, requires new platforms, protocols, and programming. Platforms must be designed around low-leakage operation, offer a richer power supply control interface for system software, and employ an unconventional energy storage hierarchy. Protocols must not only be low-power, but they must also become low-energy, which affects initial and ongoing synchronization, and periodic communications. Systems programming, and especially bootup and communications, must become low-latency, by eliminating conservative timeouts and startup dependencies, and embracing high-concurrency. Applying these principles, we show that robust, indoor, perpetual sensing is viable using off-the-shelf technology.
机译:我们研究了用能量收集叶子节点来增强电池供电的传感器网络树的问题。我们的结果表明,与当今典型的电池供电传感器相比,叶子节点尺寸较小,即使在恶劣的照明条件下,也能从周围环境中获取足够的能量来每分钟获取和传输传感器读数。但是,要实现此功能,尤其是随着叶节点规模的扩大,就需要新的平台,协议和编程。平台必须围绕低泄漏运行进行设计,为系统软件提供更丰富的电源控制接口,并采用非常规的能量存储层次结构。协议不仅必须是低功耗的,而且还必须变为低能耗的,这会影响初始和正在进行的同步以及定期通信。通过消除保守的超时和启动依赖性并采用高并发性,系统编程(尤其是启动和通信)必须变为低延迟。应用这些原理,我们证明了使用现成的技术可以实现强大的室内永久感测。

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