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Analysis of Data Aggregation Methods to avoid Data Redundancy in Wireless Sensor Network

机译:无线传感器网络中避免数据冗余的数据聚合方法分析

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Internet of Things (IoT) may be with large number of different technologies to make devices capable to interact with each other. The IoT with all these advanced technologies and devices making a rapid change of society towards easier and smarter. In IoT environment, nodes or sensors may used to collect the data and wireless communication technologies are used to transceive sensed data. IoT can involve number of sensor nodes, but with limited sensing, computational, and communication capabilities. Due to such limitations, the data size should be lower weight to improve the efficiency of the sensor nodes and bandwidth utilization of a network. To achieve network efficiency by avoiding data redundancy, the concept of data aggregation came into the picture. Data aggregation is the process of combining data from various sources and route them after removing redundancy such as to improve the overall network lifetime. When data aggregation is performed a notable communication complexity reduction rate and energy consumption reduction rate observed, hence we have studied and analyzed various Data Aggregation methods with their working methodology, features, limitations, drawbacks, results, etc. to conclude best suitable.
机译:物联网(IoT)可能具有大量不同的技术,以使设备能够相互交互。具有所有这些先进技术和设备的物联网使社会迅速朝着更轻松,更智能的方向发展。在物联网环境中,节点或传感器可用于收集数据,而无线通信技术可用于收发感测到的数据。物联网可能涉及多个传感器节点,但感测,计算和通信功能有限。由于这种限制,数据大小应具有较低的权重,以提高传感器节点的效率和网络的带宽利用率。为了通过避免数据冗余来实现网络效率,数据聚合的概念应运而生。数据聚合是合并来自各种来源的数据并在消除冗余后路由它们的过程,例如,以提高整体网络寿命。当执行数据聚合时,观察到显着的通信复杂性降低率和能耗降低率,因此,我们研究了各种数据聚合方法,并结合其工作方法,特征,局限性,缺点,结果等进行了分析,以得出最合适的结论。

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