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Cluster-based energy-efficient transmission using a new hybrid compressed sensing in WSN

机译:在无线传感器网络中使用新的混合压缩传感进行基于集群的节能传输

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Compressive sensing (CS) can reduce the energy consumption and balance the traffic load throughout the wireless sensor networks (WSN). Due to the fault tolerance and traffic load balancing of the clustering method, CS is always combined with clustering for further improvement. And hexagon clustering has some advantages over other clustering methods such as its special structure. However, the total energy consumption for data collection by using pure CS is still large. Then the hybrid CS method was proposed to obtain further energy saving, but the performance will decrease and a large amount of redundancy will be produced with the network scale increasing so that the data compression does not work well. In this paper, an analytical model of cellular clustering is put forward to study how the special hexagon structure can be combined with CS for a better performance. Then, on the basis of hexagon clustering model, a new method of hybrid CS is presented, which performs better on power consumption than other hybrid CS. Extensive simulations confirm that our method can reduce energy consumption significantly.
机译:压缩感测(CS)可以减少能源消耗并平衡整个无线传感器网络(WSN)的流量负载。由于群集方法的容错性和流量负载平衡,CS始终与群集结合使用以进一步改进。六角形聚类具有比其他聚类方法(例如其特殊结构)更优越的优势。但是,使用纯CS进行数据收集的总能耗仍然很大。然后提出了混合CS方法以进一步节省能源,但是随着网络规模的扩大,性能会降低,并且会产生大量的冗余,从而使数据压缩无法很好地工作。本文提出了一种蜂窝聚类分析模型,以研究如何将特殊的六边形结构与CS结合起来以获得更好的性能。然后,在六角形聚类模型的基础上,提出了一种混合CS的新方法,该方法在功耗上要比其他混合CS更好。大量的模拟证实了我们的方法可以显着降低能耗。

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