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An approach to data Aggregation in wireless sensor network using Voronoi fuzzy clustering algorithm

机译:基于Voronoi模糊聚类算法的无线传感器网络数据聚合方法。

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Data collected through any sensor are needed to be processed for gaining some useful information. Wireless Sensor Network (WSN) is a subclass of sensor node which is evolving as an astonishing technique in wireless communication technology for monitoring large application domains such as weather forecasting, military surveillance, medical diagnosis, fire detection alarming systems, etc. Each sensor will not be able to process itself due to the primary issue of energy (battery power) curb in WSN. Still many investigators desire to find a solution to improve the lifespan of WSN. The best way is to select an optimum head node for data aggregation to reduce the energy of data transmission for the reason that energy required for computing is more than for data transmission. This prototype shifts the attention from the outmoded address-centric approaches to data-centric approach. Data centric techniques like data aggregation via energy efficient fuzzy clustering algorithm based on Voronoi diagram is proposed in this paper. The proposed novel algorithm is a combination of Voronoi and modified Fuzzy C-Means clustering algorithm called as Voronoi Fuzzy (VF) algorithm.Cluster head (CH) for VF clustering algorithm is nominated by considering node's residual energy, distance between CH and its neighbor's sensor node and Quality of service. Furthermore, data aggregation is employed in each cluster's CH to reduce the amount of data transmission which effectively extends the network lifetime. Simulation result reveals that this method achieves agreeable performance in extending the network lifetime compared to the existing ones.
机译:通过任何传感器收集的数据都需要进行处理以获得一些有用的信息。无线传感器网络(WSN)是传感器节点的子类,在无线通信技术中正在发展成为一种惊人的技术,用于监视天气预报,军事监视,医疗诊断,火灾探测报警系统等大型应用领域。每个传感器都不会由于WSN中的主要问题(电池电量)限制,因此能够自行处理。仍然有许多研究人员希望找到一种解决方案,以提高WSN的使用寿命。最好的方法是为数据聚合选择最佳的头节点,以减少数据传输的能量,原因是计算所需的能量比数据传输所需的能量更多。该原型将注意力从过时的以地址为中心的方法转移到以数据为中心的方法。提出了一种基于Voronoi图的以能量为中心的模糊聚类算法等以数据为中心的数据聚合技术。该算法是Voronoi算法与改进的Fuzzy C-Means聚类算法(称为Voronoi Fuzzy(VF)算法)的结合.VF聚类算法的簇头(CH)通过考虑节点的剩余能量,CH与相邻传感器之间的距离来指定节点和服务质量。此外,在每个群集的CH中采用数据聚合以减少数据传输量,从而有效地延长了网络寿命。仿真结果表明,与现有方法相比,该方法在延长网络寿命方面取得了令人满意的性能。

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