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Energy-Efficient Data Gathering in Wireless Sensor Networks with Asynchronous Sampling

机译:具有异步采样功能的无线传感器网络中的节能数据收集

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A low sampling rate leads to reduced congestion and hence energy consumption in the resource-constrained wireless sensor networks. In this article, we propose asynchronous sampling that shifts the sampling time instances of sensor nodes from each other. For lossy data gathering scenarios, the proposed approach provides more information about the physical phenomena in terms of increased entropy at a low sampling rate. For lossless data gathering scenarios, on the other hand, the sampling rate is lowered without sacrificing critical knowledge required for signal reconstruction. As lower sampling rates lead to smaller energy consumption for processing and transmitting the collected sensory data, the proposed asynchronous sampling strategies are capable of achieving a better trade-off between the lifetime of the network and the quality of collected information. In addition to mathematical analysis, simulation results based on real data also verify the benefits of our asynchronous sampling.
机译:低采样率可减少拥塞,从而减少资源受限的无线传感器网络的能耗。在本文中,我们提出了异步采样,该异步采样使传感器节点的采样时间实例彼此偏移。对于有损数据收集方案,建议的方法在低采样率下以增加的熵的形式提供有关物理现象的更多信息。另一方面,对于无损数据收集方案,在不牺牲信号重建所需的关键知识的情况下降低了采样率。由于较低的采样率会导致处理和传输收集的感官数据的能耗降低,因此,所提出的异步采样策略能够在网络的使用寿命与收集的信息的质量之间取得更好的折衷。除了数学分析之外,基于真实数据的仿真结果还证明了我们异步采样的好处。

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