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Energy management in battery-powered sensor networks with reconfigurable computing nodes

机译:具有可重配置计算节点的电池供电传感器网络中的能源管理

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In this work we have investigated the benefits of using reconfigurable computing (RC) nodes in sensor networks. We assumed that several sensor nodes are deployed randomly in a field, to form a sensor network and each sensor in the network sends its data in the form of packets to a single energy-rich sink node. We also assumed that each sensor node has reconfigurable fabric which can be configured by downloading a bitstream. In contrast to the contemporary work in energy management for sensor networks, we use an accurate analytical battery model to simulate the battery consumption of each node in the network. We have written several simulation models to study various sensor network parameters when the underlying nodes are adaptive in nature instead of traditional, non-adaptive processor based, fixed implementation. As the remaining battery-capacity of our RC based node decreases, it changes its behavior by reconfiguring itself to lower powered implementations successively, thereby extending the sensor network lifetime as a whole. Our results indicate that the network life is increased by up to five times and the number of packets generated by the sensor nodes and received at the sink node more than quadrupled for RC based nodes when compared to fixed processor based node implementation.
机译:在这项工作中,我们研究了在传感器网络中使用可重构计算(RC)节点的好处。我们假设在现场随机部署了几个传感器节点,以形成一个传感器网络,并且网络中的每个传感器都以数据包的形式将其数据发送到单个能量丰富的接收器节点。我们还假定每个传感器节点都具有可重新配置的结构,可以通过下载比特流来对其进行配置。与传感器网络能源管理的当代工作相比,我们使用精确的分析电池模型来模拟网络中每个节点的电池消耗。当基础节点本质上是自适应的,而不是基于传统的非自适应处理器的固定实现时,我们已经编写了几种仿真模型来研究各种传感器网络参数。随着基于RC的节点的剩余电池容量减少,它会通过将其自身重新配置为低功耗的实现方式来改变其行为,从而整体上延长了传感器网络的使用寿命。我们的结果表明,与基于固定处理器的节点实现相比,对于基于RC的节点,网络寿命增加了五倍,并且由传感器节点生成并在接收器节点处接收到的数据包数量增加了四倍。

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