论文标题
边界节点的检测和复杂非凸的临时网络的展开
Boundary Node Detection and Unfolding of Complex Non-Convex Ad Hoc Networks
论文作者
论文摘要
复杂的非Convex临时网络（CNCAH）包含相交的多边形和边缘。在许多情况下，这些网络的布局并不完全是凸的。在本文中，我们提出了一种基于Kamada-kawai的算法，称为W-KK-MS用于边界节点检测问题，该算法能够使节点位置对齐，同时在从输入网络拓扑中产生视觉图的高灵敏度，特异性和准确性。本文提出的算法选择并为每次迭代中的顶级节点分配权重，以加快节点的更新过程。我们还提出了一种新的方法来检测和展开CNCAH网络中的堆叠区域。实验结果表明，所提出的算法可以在CNCAH网络中的边界节点检测中实现快速收敛，并能够成功展开堆叠区域。本文还描述了称为ELNET的原型系统的设计和实现，用于分析CNCAH网络。 ELNET系统能够生成用于测试，与力定向算法集成以及可视化和分析算法结果的合成网络。
Complex non-convex ad hoc networks (CNCAH) contain intersecting polygons and edges. In many instances, the layouts of these networks are not entirely convex in shape. In this article, we propose a Kamada-Kawai-based algorithm called W-KK-MS for boundary node detection problems, which is capable of aligning node positions while achieving high sensitivity, specificity, and accuracy in producing a visual drawing from the input network topology. The algorithm put forward in this article selects and assigns weights to top-k nodes in each iteration to speed up the updating process of nodes. We also propose a novel approach to detect and unfold stacked regions in CNCAH networks. Experimental results show that the proposed algorithms can achieve fast convergence on boundary node detection in CNCAH networks and are able to successfully unfold stacked regions. The design and implementation of a prototype system called ELnet for analyzing CNCAH networks is also described in this article. The ELnet system is capable of generating synthetic networks for testing, integrating with force-directed algorithms, and visualizing and analyzing algorithms' outcomes.
