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Boundary static clustering target tracking in wirless sensor networks

机译:无线传感器网络中的边界静态聚类目标跟踪

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WSNs have been impressive progress in recent years and target tracking is one of the most important applications in wireless sensor networks. Clustering is one of the efficient methods for target tracking application that has ability of scalability and flexibility. In wireless sensor networks with limited recourses, energy is a challenging problem. Thus, energy is very important factor and also the other important factor is tracking accuracy in target tracking applications, thus for designing algorithm the trade-off between energy and tracking accuracy should be considered. In this research we propose an energy efficient cluster based target tracking method by using boundary static clusters (BCTT). The simulation results achieved using the Castalia simulator shows that, BCTT has 48% decreases in average energy consumption compared with hybrid method (HCTT, HCMTT).
机译:近年来,无线传感器网络取得了令人瞩目的进展,目标跟踪是无线传感器网络中最重要的应用之一。群集是具有可伸缩性和灵活性的目标跟踪应用程序的有效方法之一。在资源有限的无线传感器网络中,能源是一个具有挑战性的问题。因此,能量是非常重要的因素,另一个重要因素是目标跟踪应用中的跟踪精度,因此,在设计算法时,应考虑能量和跟踪精度之间的权衡。在这项研究中,我们提出了一种使用边界静态聚类(BCTT)的基于节能聚类的目标跟踪方法。使用Castalia模拟器获得的模拟结果表明,与混合方法(HCTT,HCMTT)相比,BCTT的平均能耗降低了48%。

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