From rateless to distanceless: enabling sparse sensor network deployment in large areas
From rateless to distanceless: enabling sparse sensor network deployment in large areas
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DOI：
10.1145/2668332.2668335
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Wan Du;Zhenjiang Li;J. Liando;Mo Li
中科院分区：
文献类型：
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作者：
Wan Du;Zhenjiang Li;J. Liando;Mo Li
针对大面积稀疏部署的无线传感器网络，提出了一种无距离组网方法。通过利用无比率编码，我们提供了无距离传输，以扩大传感器微尘的通信范围，并充分利用网络的多样性。我们解决了各种实际的挑战，以适应资源受限的传感器微尘上的无比率编码，并设计了一个通信协议，以有效地协调无距离链路传输。我们提出了一个新的路由选择指标（预期无距离传输时间），并进一步使无距离传输适应低占空比传感器网络。我们在TinyNode平台上的TinyOS中实现了所提出的方案，并在实际项目中部署了传感器网络，其中12个测风传感器安装在2.5km * 3.0km的大型城市水库周围，以监测现场风分布。大量的实验表明，我们提出的方案显着优于国家的最先进的方法，在稀疏传感器网络中的数据收集。
This paper presents a distanceless networking approach for wireless sensor networks sparsely deployed in large areas. By leveraging rateless codes, we provide distanceless transmission to expand the communication range of sensor motes and fully exploit network diversity. We address a variety of practical challenges to accommodate rateless coding on resource-constrained sensor motes and devise a communication protocol to efficiently coordinate the distanceless link transmissions. We propose a new metric (expected distanceless transmission time) for routing selection and further adapt the distanceless transmissions to low duty-cycled sensor networks. We implement the proposed scheme in TinyOS on the TinyNode platform and deploy the sensor network in a real-world project, in which 12 wind measurement sensors are installed around a large urban reservoir of 2.5km * 3.0km to monitor the field wind distribution. Extensive experiments show that our proposed scheme significantly outperforms the state-of-the-art approaches for data collection in sparse sensor networks.