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Partition Based Strategic Node Placement and Efficient Communication Method for WSN

机译:WSN的基于分区的战略节点布局和高效通信方法

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Today, the Wireless Sensor Network (WSN) is having a very vast area in the various field of research and development. The main focus of WSN is to intensify the existence of WSN by decreasing the energy depletion. The lifetime of WSN is depended on many factors like energy depletion, transmission range, communication range and sensing range. But mainly, the lifetime of WSN is highly dependent on energy utilization. So we have to reduce the wastage of energy of sensor nodes. There is a way that can save the energy of nodes by placing them in an elegant manner. In this paper, we propose an Advanced Specific Node Formation (ASNF) strategy and communication method for WSNs. This strategy is performed in four rounds. In the first round, the sensor nodes are positioned in the circular pattern in inner region. In the second round, we positioned the nodes in hexagonal and pentagonal patterns called hexa circular node formation and penta circular node formation respectvely in outer region. The partition of whole area in distinct pattern is performed in third round. After that, the selection of CHs in respective areas takes place in fourth round. The selection of a Cluster Heads (CHs) can be based on many parameters like residual energy and the distance from the nodes etc. Particularly, under this strategy, we select the CHs with the premises of optimum energy. In this way, the whole area will be covered with least nodes. With these nodes, we can aggregate the information. So, with the help of this strategy, we can assess higher proficiency for network lifetime and energy depletion. The simulation results shows higher proficiency of energy depletion, dead node and delay etc.
机译:如今,无线传感器网络(WSN)在各个研究和开发领域中都有非常广阔的领域。 WSN的主要焦点是通过减少能量消耗来增强WSN的存在。无线传感器网络的寿命取决于许多因素,例如能量消耗,传输范围,通信范围和感应范围。但主要而言,无线传感器网络的寿命高度依赖于能源利用。因此,我们必须减少传感器节点能量的浪费。有一种方法可以通过以优雅的方式放置节点来节省能量。在本文中,我们提出了一种针对WSN的高级特定节点形成(ASNF)策略和通信方法。此策略分四轮执行。在第一轮中,传感器节点在内部区域中以圆形图案放置。在第二轮中,我们分别在外部区域将节点分别定位为六边形和五边形,分别称为六边形圆形结点和五边形圆形结点。在第三轮中以不同的模式划分整个区域。此后,在第四轮中选择各个区域的CH。簇头(CH)的选择可以基于许多参数,例如剩余能量和与节点之间的距离等。特别是,在这种策略下,我们以最佳能量为前提选择CH。这样,整个区域将被最少的节点覆盖。通过这些节点,我们可以汇总信息。因此,借助此策略,我们可以评估网络寿命和能量消耗的更高水平。仿真结果表明,能量损耗,死节点和时延等方面的熟练度更高。

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