This article focuses on the problem of scheduling the optimal paths of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize the travel distance and balance the energy consumption and the data gathering latency in wireless sensor networks for smart cities. To partition the network for the multiple mobile elements and compute the trajectories of the multiple mobile elements, we utilize the sensor’s communication range and construct a multiple mobile elements scheduling problem. A heuristic mobile data gathering approach is proposed to solve this problem, which includes the following three steps. The sensor nodes are preliminarily partitioned into four levels, and then the clusterheads are further partitioned, and the traveling tour is scheduled for each cluster. After the first two steps, all the sensor nodes are partitioned reasonably for the multiple mobile elements. In the last step, the traveling tour is scheduled for each cluster, and the meeting point of each clusterhead is determined. We compare the proposed heuristic mobile data gathering with the existing approaches. The results indicate that the travel distance and the data gathering latency are reduced significantly, which further validates that the communication range is beneficial to minimize the travel distance.

中文翻译：

---

基于轨迹控制的无线传感器网络启发式移动数据采集

本文重点研究智能城市无线传感器网络中多个移动元素（例如机器人、车辆等）的最优路径调度问题，以最小化出行距离并平衡能耗和数据收集延迟。为了为多个移动元素划分网络并计算多个移动元素的轨迹，我们利用传感器的通信范围并构建了一个多移动元素调度问题。为了解决这个问题，提出了一种启发式移动数据收集方法，包括以下三个步骤。传感器节点初步划分为四级，然后进一步划分簇头，为每个簇安排旅行。在前两步之后，所有的传感器节点都为多个移动元素进行了合理的划分。在最后一步，为每个簇安排旅行，并确定每个簇头的会合点。我们将提议的启发式移动数据收集与现有方法进行比较。结果表明，旅行距离和数据收集延迟显着降低，这进一步验证了通信范围有利于最小化旅行距离。