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A coverage-enhance scheduling algorithm for 3D directional sensor networks

机译:一种覆盖增强调度算法3D方向传感器网络

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Directional Sensor Networks (DSNs) are the special type of Wireless Sensor Networks (WSNs), which take use of the directional sensing nodes like image/video, ultrasonic wave. Most of coverage studies of DSNs focus on 2D directional sensing models. However, the 3D sensing models are more complex but closer to the real situation. So a noble 3D directional sensing model is established in this paper, and the key parameters are calculated precisely. To enhance the 3D coverage rate of DSNs, a Greedy Iteration based area coverage-enhance Scheduling algorithm (GI-ACE) is also proposed. In the proposed algorithm, the local optimum of one certain sensor node is not the only consideration, the global local optimum is also scheduled. Otherwise, the simulation experiments are designed to evaluate the performance of the proposed algorithm, and the results show that GI-ACE is effective in coverage-enhancing compared with other traditional algorithms.
机译:定向传感器网络(DSN)是特殊类型的无线传感器网络(WSN),其采用类似图像/视频,超声波的定向感测节点。 DSN的大多数覆盖研究专注于2D方向传感模型。然而,3D感测模型更复杂但更接近真实情况。因此,在本文中建立了一种贵族3D定向传感模型,并且精确地计算了关键参数。为了增强DSN的3D覆盖率,还提出了一种贪婪的基于迭代的区域覆盖增强调度算法(GI-ACE)。在所提出的算法中,一个特定传感器节点的本地最佳最佳值不是唯一的考虑因素,还在调度全局本地最佳。否则,仿真实验旨在评估所提出的算法的性能,结果表明,与其他传统算法相比,GI-ACE在覆盖增强方面是有效的。

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