定常流环境中基于能量的Voronoi划分
Energy-Based Voronoi Partition in Constant Flow Environments
摘要：
众所周知，能源成本会极大地影响电池供电的传感器网络在河流或海洋等偏远环境中的部署。出于这一动机，我们在这里提出了一个基于能量的度量和关联基于能量的Voronoi分区与移动车辆在恒定的流量。该度量对应于车辆在流环境中从一个点移动到另一个点所需的最小能量，并且由此产生的分区可以由车辆在诸如任务分配和覆盖的协作控制任务中使用。基于基于圆盘和渐近近似的Voronoi区域，我们确定一个子集（或下界）和超集（或上界）的代理的Voronoi邻居。然后，我们表明，通过模拟，上界是紧的，其基数保持有界的发电机的数量增加。最后，我们提出了有效的算法来计算的上界（特别是当发电机动态变化），这使得快速计算的Voronoi区域。
英文摘要：
As is well known, energy cost can greatly impact the deployment of battery-powered sensor networks in remote environments such as rivers or oceans. Motivated by this, we propose here an energy-based metric and associate energy-based Voronoi partitions with mobile vehicles in constant flows. The metric corresponds to the minimum energy that a vehicle requires to move from one point to another in the flow environment, and the resulting partition can be used by the vehicles in cooperative control tasks such as task assignment and coverage. Based on disk-based and asymptote-based approximations of the Voronoi regions, we determine a subset (or lower bound) and superset (or upper bound) of an agent's Voronoi neighbors. We then show that, via simulations, the upper bound is tight and its cardinality remains bounded as the number of generators increases. Finally, we propose efficient algorithms to compute the upper bound (especially when the generators dynamically change), which enables the fast calculation of Voronoi regions.
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