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Adaptive clustering with transmission power control in wireless sensor networks

机译:无线传感器网络中具有传输功率控制的自适应群集

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Transmission power control allows a node to dynamically change its power level for energy saving. Many adaptive clustering algorithms propose to use different power levels for clustering. However, the transmission power control had never been integrated as a step in the algorithms. Analysis of the algorithm is done based on assumption that nodes are capable of switching between different power levels. This paper attempts to highlight the possible overhead incurred due to applying power control algorithm in an adaptive clustering in Wireless Sensor Networks. The side effects of executing power control algorithm every time cluster heads rotate can possibly cancel all performance gained if communication overhead is not taken into account. This paper identifies the energy overhead and delay time as two main factors to consider for integration to be successfully implemented. We perform analysis of these factors on existing clustering algorithms such as EECS and MOECS. The analytical results show that the energy overhead is dependent on network size and the number of cluster head candidates. We also show that the delay time involved in switching power levels has to remain low for effective clustering process.
机译:传输功率控制允许节点动态更改其功率级别以节省能源。许多自适应聚类算法建议使用不同的功率水平进行聚类。但是,传输功率控制从未集成为算法的一个步骤。基于节点能够在不同功率级别之间切换的假设进行算法分析。本文试图强调由于在无线传感器网络的自适应集群中应用功率控制算法而可能引起的开销。如果不考虑通信开销,则每次簇头旋转时执行功率控制算法的副作用可能会抵消所获得的所有性能。本文确定了能量开销和延迟时间是要成功实现集成要考虑的两个主要因素。我们对现有的聚类算法(例如EECS和MOECS)进行这些因素的分析。分析结果表明,能量开销取决于网络大小和候选簇头数量。我们还表明,对于有效的群集过程,切换功率电平所涉及的延迟时间必须保持较低。

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