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Efficient Data Collection with Sampling in WSNs: Making Use of Matrix Completion Techniques

机译:在无线传感器网络中通过采样进行有效的数据收集:利用矩阵完成技术

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Data collection is of paramount importance in many applications of wireless sensor networks (WSNs). Especially, to accommodate ever increasing demands of signal source coding applications, the capacity of processing multi-user data query is crucial in WSNs where the efficiency is one key consideration. To that end, this paper presents EDCA: an Efficient Data Collection Approach for data query in WSNs, which exploits recent matrix completion techniques. Specifically, for the efficiency of energy consumption, we randomly select a part of nodes from the sensor network to sample at each time instance and directly forward the data to the sink. Then, to recover the data precisely, we shift the rank minimization problem, which is NP-hard, to a convex optimization one. Compared with the centralized scheme, energy consumption using EDCA is significantly reduced due to lower sampling rate and fewer packets to transmit. The experimental results demonstrate that EDCA significantly outperforms the existing naive method in terms of energy consumption and the introduced errors are quite trivial.
机译:在无线传感器网络(WSN)的许多应用中,数据收集至关重要。特别是,为了适应信号源编码应用程序不断增长的需求,在效率是一个关键考虑因素的WSN中,处理多用户数据查询的能力至关重要。为此,本文提出了EDCA:一种用于WSN中数据查询的有效数据收集方法,该方法利用了最新的矩阵完成技术。具体来说,为了提高能源消耗效率,我们从传感器网络中随机选择一部分节点在每个时间点进行采样,然后将数据直接转发到接收器。然后,为了精确地恢复数据,我们将秩最小化问题(NP难)转移到凸优化问题上。与集中式方案相比,由于较低的采样率和较少的数据包传输,使用EDCA的能耗大大降低。实验结果表明,EDCA在能耗方面明显优于现有的简单方法,并且引入的误差也很小。

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