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

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. In each experimental instance, the initial optimal communication topology without faults is obtained by the same algorithm called CTOA-3DPF-LC, both agents suffering agent loss and the communication links suffering link loss are randomly generated in the initial optimal communication topology, and the reconstructed communication topology under fault is obtained by the existing algorithms and ECTRA-3DPF-FC. Under the same experimental data set, number of agents, and formation shape, the set of faults in the experimental instance with a higher fault ratio includes that with a lower fault ratio.

Meanwhile, to analyze the impact of network heterogeneity on the performance of ECTRA-3DPF-FC, another three data sets F, G and H are designed. The three data sets are very similar to data set E, with the only difference being that the node distributions in these three data sets are uniform distribution, Gaussian distribution, and cluster distribution, respectively. Specifically, in the Gaussian distribution, the center is the center of the cube area (5000×5000×5000), with a mean of 0 and a standard deviation of 1/5 of the cube edge length. In the cluster distribution, the number of clusters is 5, and the radius of each cluster is 200.

Moreover, to analyze the impact of topological properties of fault nodes on the performance of ECTRA-3DPF-FC, another two data sets I and J are designed. The two data sets are very similar to data set A, with the only difference being that the faulty nodes in these two data sets are the hub nodes and the leaf nodes, respectively. Specifically, in data set I, the faulty nodes are selected in descending order of their degree in the communication topology. In data set J, the faulty nodes are selected in ascending order of their degree in the communication topology.