The Experimental Data Sets and Appendix of the paper “Communication Topology Reconstruction for a Three-Dimensional Persistent Formation with Fault Constraints”

According to the different proportion of agent loss and link loss in faults, five experimental data sets are designed. Among them, the fault type corresponding to data set A is agent loss where the proportion of link loss in faults is 0%, the fault type of data set B, C and D is agent & link loss where the proportion of link loss in faults is 25%, 50% and 75% respectively, and the fault type of data set E is link loss where the proportion of link loss in faults is 100%.
In each experimental data set, experimental instances are generated under different number of agents, formation shape, and fault ratio. Specifically, the number of agents is 20, 30, 40, and 50 respectively, 5 different formation shapes are randomly generated in the area of 5000×5000×5000 under the same number of agents, and the fault ratio is 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, and 0.50 respectively. Therefore, the total number of experimental instances is 5×4×5×10 = 1000. Specifically, the fault ratio under agent loss is the ratio of the number of agents suffering agent loss to the number of all agents in the initial optimal communication topology, the fault ratio under link loss is the ratio of the number of communication links suffering link loss to the number of all communication links in the initial optimal communication topology, and the fault ratio under agent & link loss is the sum of fault ratio under agent loss and fault ratio under link loss, where the fault ratio under agent loss is equal to the fault ratio under link loss.
Each experimental instance has an identifier that includes the corresponding data set, the number of agents and the formation shape. For example, A-20-1 indicates that this experimental instance belongs to data set A, its number of agents is 20, and its formation shape is the first one. For each experimental instance, the corresponding formation communication cost of the solution obtained by each algorithm and its calculation time are listed in the Appendix.

依据故障中智能体损失与链路损失的不同比例，设计了五个实验数据集。其中，数据集A对应故障类型为智能体损失，故障中链路损失的比例为0%；数据集B、C和D的故障类型为智能体与链路损失，故障中链路损失的比例分别为25%、50%和75%；数据集E的故障类型为链路损失，故障中链路损失的比例为100%。在每一个实验数据集中，根据不同的智能体数量、编队形状和故障比率生成实验实例。具体而言，智能体数量分别为20、30、40和50，在相同数量的智能体下，随机生成5种不同的编队形状，该形状生成于5000×5000×5000的区域范围内，故障比率分别为0.05、0.10、0.15、0.20、0.25、0.30、0.35、0.40、0.45和0.50。因此，实验实例的总数为5×4×5×10，即1000个。具体而言，智能体损失下的故障比率是遭受智能体损失的智能体数量与初始最优通信拓扑中所有智能体数量的比率；链路损失下的故障比率是遭受链路损失的通信链路数量与初始最优通信拓扑中所有通信链路数量的比率；智能体与链路损失下的故障比率是智能体损失故障比率和链路损失故障比率的总和，其中智能体损失故障比率等于链路损失故障比率。每个实验实例均具有一个标识符，该标识符包含对应的数据集、智能体数量和编队形状。例如，A-20-1表示该实验实例属于数据集A，其智能体数量为20，其编队形状为第一种。对于每个实验实例，列出由每种算法获得的解决方案对应的编队通信成本及其计算时间，详见附录。