Aerial-Ground Cost Tradeoff for Multi-UAV-Enabled Data Collection in Wireless Sensor Networks
Aerial-Ground Cost Tradeoff for Multi-UAV-Enabled Data Collection in Wireless Sensor Networks
复制标题
无线传感器网络中多无人机数据采集的空地成本权衡
DOI：
10.1109/tcomm.2019.2962479
复制
发表时间：
2020-03-01
影响因子：
8.3
通讯作者：
Zeng, Yong
中科院分区：
文献类型：
--
作者：
Zhan, Cheng;Zeng, Yong
无人机 (UAV) 通信已成为无线传感器网络 (WSN) 中高效数据收集的一项颇具吸引力的技术。本文考虑了多架无人机从地面上的一组传感器节点（SN）收集数据的场景。我们研究了空中成本（由所有无人机的推进能耗和运行成本定义）与地面成本（定义为所有SN的能耗）之间的基本权衡。为了表征这种权衡，通过优化 UAV 轨迹、唤醒时间分配以及所有 SN 的发射功率，制定了一个优化问题，以最小化上述两个成本的加权和。由于所提出的问题是非凸的，因此一般情况下很难得到最优解决。为了解决这个问题，我们将其分解为两个子问题：无人机轨迹和唤醒时间分配优化，以及SN发射功率优化。我们提出了一种迭代算法，通过利用连续凸逼近和交替优化技术来解决这两个子问题。此外，提出了一种利用多旅行商问题（MTSP）技术设计无人机初始轨迹的新方法。进行仿真是为了证实我们的研究，并展示所提出的设计实现的灵活权衡，以实现无人机和SN之间的成本平衡。
Unmanned aerial vehicle (UAV)-enabled communication has emerged as an appealing technology for efficient data collection in wireless sensor networks (WSNs). This paper considers a scenario where multiple UAVs collect data from a group of sensor nodes (SNs) on the ground. We study the fundamental tradeoff between the aerial cost, which is defined by the propulsion energy consumption and operation costs of all UAVs, and the ground cost, which is defined as the energy consumption of all SNs. To characterize such a tradeoff, an optimization problem is formulated to minimize the weighted sum of the above two costs, by optimizing the UAV trajectory jointly with wake-up time allocation, as well as the transmit power of all SNs. As the formulated problem is non-convex, it is difficult to be optimally solved in general. To tackle this issue, we decouple it into two sub-problems: UAV trajectory and wake-up time allocation optimization, as well as SN transmit power optimization. We propose an iterative algorithm to solve the two sub-problems by leveraging successive convex approximation and alternating optimization techniques. In addition, a new approach is proposed to design the UAV initial trajectory with multiple travelling salesman problem (MTSP) technique. Simulations are conducted to corroborate our study and show the flexible tradeoff achieved by the proposed design for cost balance between UAVs and SNs.