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An image processing inspired mobile sink solution for energy efficient data gathering in wireless sensor networks

机译：灵感源自图像处理的移动接收器解决方案，用于无线传感器网络中的节能数据收集

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摘要

This paper presents a gradient-based multi-hop clustering protocol combined with a mobile sink (MS) solution for efficient data gathering in wireless sensor networks. The main insight for the clustering algorithm is drawn from image processing field and namely from the watershed transform, widely used for image segmentation. The proposed algorithm creates multi-hop clusters whose cluster heads (CHs) as well as cluster members near the CHs have high energy reserves. Specifically, the energy of the sensors in a cluster increases progressively as getting closer to the CH. As the nodes closer to the CH are most burdened with relaying of data from other cluster members, the higher levels of available energy at these nodes prolong the network lifetime eventually. After cluster formation, a MS periodically visits each CH and collects the data from cluster members already gathered at the CH. Simulation results show the higher performance of the proposed scheme in comparison to other competent approaches in the literature.
机译：本文提出了一种基于梯度的多跳群集协议，结合了移动接收器（MS）解决方案，可在无线传感器网络中高效地收集数据。聚类算法的主要见解来自图像处理领域，即分水岭变换，它广泛用于图像分割。所提出的算法创建了多跳簇，其簇头（CH）以及CH附近的簇成员具有较高的能量储备。具体而言，簇中传感器的能量随着与CH的接近而逐渐增加。由于距离CH较近的节点最负担来自其他群集成员的数据中继，因此这些节点上更高级别的可用能量最终会延长网络寿命。在集群形成之后，MS定期访问每个CH，并从已经在CH处收集的集群成员收集数据。仿真结果表明，与文献中的其他有效方法相比，该方案具有更高的性能。

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