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Soft computing approach based energy and correlation aware cooperative data collection for wireless sensor network

机译:基于软计算方法的无线传感器网络的能量和相关意识的知识数据集合

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摘要

Energy plays the predominant constraint in wireless sensor network (WSN) hence, an energy and correlation aware cooperative data collection (ECCDC) method of soft computing approach has been discussed in this work. This work is an attempt to maximize the life span of the network by identifying and rectifying the major energy exploiting activities of WSN and it also defines a hierarchical network structure with balanced clusters and energy harvesting sensor nodes. These sensor nodes select the Cluster Heads (CHs) among themselves using a low overhead passive clustering approach. The cluster balancing has been performed by acknowledging only the most deserved sensor nodes as their members. The members co-operatively collect the data from the region of interest. During every time slot, the cluster members are chosen for reporting, based on the mutual correlation, link quality of the member with the CH and the residual energy of the member nodes. The fraction of data collected at the CH is then sent through the optimized inter-cluster paths to the sink, wherein the received data are used for estimation, based on the node's position and correlation pattern. This proposed system of optimize method reduces the energy consumed, due to the transmission of redundant data and the data loss by preferring optimized data paths.
机译:能量在无线传感器网络(WSN)中起主要的约束,因此,在这项工作中讨论了软计算方法的能量和相关意识协同数据收集(ECCDC)方法。这项工作是一种尝试通过识别和纠正WSN的主要能量利用活动来最大化网络的寿命,并且还定义了具有平衡簇和能量收集传感器节点的分层网络结构。这些传感器节点使用低开销被动聚类方法在自己选择群集头(CHS)。通过确认最应有的传感器节点作为其成员,已经执行了群集平衡。成员共同可操作地收集来自感兴趣区域的数据。在每次时隙期间,基于互相关,基于与CH的成员的链路质量和成员节点的剩余能量来选择集群成员。然后通过对接收器的优化的簇路径发送在CH处收集的数据的分数,其中,基于节点的位置和相关模式,所接收的数据用于估计。这一提出的优化方法系统减少了由于通过优化的数据路径传输冗余数据和数据丢失而消耗的能量。

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