Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks.
Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks.
复制标题
DOI：
10.3390/s17020413
复制
发表时间：
2017-02-20
期刊：
影响因子：
--
通讯作者：
Soyturk M
中科院分区：
文献类型：
--
作者：
Rashed S;Soyturk M
无线传感器网络(WSN)中的传感器节点可以分散在一个遥感区域(例如，人类难以访问的区域)。在这类网络中，数据收集成为主要问题之一。连接到每个传感器节点并及时检索信息带来了新的挑战。在如此大规模的无线传感器网络中，使用移动汇点--特别是无人驾驶飞行器(UAV)--是覆盖区域和访问每个传感器节点的最方便的方法。然而，无人机的操作取决于一些参数，如耐力时间、高度、速度、使用中的无线电类型和路径。在本文中，我们探索了不同的无人机移动模式，沿着不同的路径对作业区进行扫描，以便在移动汇聚所需的最少时间内寻找具有最大覆盖节点数量的最佳区域覆盖。我们还引入了一种新的度量来描述在选择合适的移动模式时最大化覆盖节点和最小化操作时间之间的权衡。为了比较和评估系统的性能，使用了一个逼真的仿真环境。我们给出了探索的无人机机动性模式的性能结果。这些结果对于在最大化覆盖节点和最小化操作时间之间进行权衡以选择合适的移动性模式是非常有用的。
Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, data collection becomes one of the major issues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage—especially Unmanned Aerial Vehicles (UAVs)—is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern.