| （英） |
In this paper, we consider a deployment scheduling problem taking into account the connectivity of drones in drone communication networks. In the drone communication networks, to effectively collect data from user nodes on the ground, the drones should be deployed at the proper positions. Moreover, the collected data is delivered to a base station, so that it is desirable that the base station and the drones are connected. Therefore, in this paper, we propose a drone deployment method, where the base station and drones are connected every time. Specifically, we propose two deployment methods : One is an ILP(Integer Linear Programming)-based deployment method and the other one is a $epsilon$-greedy based deployment method. In the ILP-based deployment method, the positions of the drones are determined by solving an ILP in which the objective function is the total number of nodes that can collect data at each time. In the $epsilon$-greedy based deployment method, among the neighboring areas which is adjacent to the areas where the drones are already placed, the neighboring area with the largest user nodes is selected with probability 1-$epsilon$, and other neighboring areas are randomly selected with probability $epsilon$. Through numerical experiments, we show that these deployment methods can efficiently collect data from user nodes. |