Abstract：
During these years, the 3D node coverage of heterogeneous wireless sensor networks that are closer to the actual application environment has become a strong focus of research. However, the direct application of traditional two-dimensional planar coverage methods to three-dimensional space suffers from high application complexity, a low coverage rate, and a short life cycle. Most methods ignore the network life cycle when considering coverage. The network coverage and life cycle determine the quality of service (QoS) in heterogeneous wireless sensor networks. Thus, energy-efficient coverage enhancement is a significantly pivotal and challenging task. To solve the above task, an energy-efficient coverage enhancement method, VKECE-3D, based on 3D-Voronoi partitioning and the K-means algorithm is proposed. The quantity of active nodes is kept to a minimum while guaranteeing coverage. Firstly, based on node deployment at random, the nodes are deployed twice using a highly destructive polynomial mutation strategy to improve the uniformity of the nodes. Secondly, the optimal perceptual radius is calculated using the K-means algorithm and 3D-Voronoi partitioning to enhance the network coverage quality. Finally, a multi-hop communication and polling working mechanism are proposed to lower the nodes\' energy consumption and lengthen the network\'s lifetime. Its simulation findings demonstrate that compared to other energy-efficient coverage enhancement solutions, VKECE-3D improves network coverage and greatly lengthens the network\'s lifetime.
摘要：
在这些年里,更加贴近实际应用环境的异构无线传感器网络三维节点覆盖成为研究的重点。然而,传统的二维平面覆盖方法直接应用于三维空间,覆盖率低，和短生命周期。大多数方法在考虑覆盖时都忽略了网络生命周期。网络覆盖和生命周期决定了异构无线传感器网络中的服务质量(QoS)。因此，节能覆盖增强是一项非常关键和具有挑战性的任务。为了解决上述任务，一种节能的覆盖增强方法，VKECE-3D,提出了基于3D-Voronoi分割和K-means算法的算法。活动节点的数量保持在最低限度,同时保证覆盖。首先,基于随机的节点部署，使用高破坏性多项式变异策略对节点进行两次部署,以提高节点的均匀性。其次,利用K-means算法和3D-Voronoi分区计算最优感知半径,以提高网络覆盖质量。最后,提出了一种多跳通信和轮询工作机制，以降低节点的能耗并延长网络的寿命。其仿真结果表明，与其他节能覆盖增强解决方案相比，VKECE-3D提高了网络覆盖并大大延长了网络的寿命。
