# A Community-Based Construct Method for an Inter-Satellite Communication Network of Satellite Swarm
## 5 Simulation Analyses  
### Simulation Analyses for the Construction of an ICNS  
The satellite swarm consists of 30 satellites [26]:  
* Three geosynchronous orbit satellites are at an altitude of 35,786 km and longitude of 80 \({}^{\circ}\)E, 110.5 \({}^{\circ}\)E, and 140 \({}^{\circ}\)E, respectively, and they are numbered from 1 to 3;
* Three inclined geosynchronous orbit satellites are spaced with 120 \({}^{\circ}\) phase intervals at an attitude of 35,786 km and inclination of 55 \({}^{\circ}\), and they are numbered from 4 to 6;
* Twenty-four medium earth orbit satellites constitute a 24/3/1 walker constellation with an altitude of 21,528 km and an inclination of 55 \({}^{\circ}\), and they are numbered from 7 to 30. The satellite constellation above is also used in [2; 2; 3; 4; 5; 6; 7].  
The length of the task time interval was set as 4 min from 17:17:00 to 17:21:00 on 16 August 2015. The state period could be set to 1 min or 2 min according to the visibility between satellites during the task time interval. Each slot lasted for 3 s, which is the rule of thumb introduced by the authors in [27]. Therefore, we designed four simulation groups, as shown in Table 1. Simulation group 2 and simulation group 4 used the method in Section 3, which did not improve the construction of ICNS. On the contrary, simulation group 1 and simulation group 3 used the method in Section 4 to improve the construction of the ICNS. The proposed methods were implemented in Java.  
The ICNSs that were constructed in four simulation groups in Table 1 are illustrated in Figure 4. As the PLN for each slot in each simulation group had a perfect matching, there was \(\theta=\frac{1}{2}\Theta=15\) in the ICNS for each slot. As Figure 4b,d show, each satellite in the ICNSs without improvement had an established ISL with the same satellite during the entire state period. These terrible situations have never happened in ICNSs with improvements, as is shown in Figure 4a,c. We only analyzed the results of simulation group 1 and simulation group 3, as the results of simulation group 2 and simulation group 4 were quite disappointing.  
The structural entropies of CCLCs that were selected to become edge sets of ICNSs are illustrated in Figure 5. The CCLC for each one of the first 20 slots in simulation group 3 had the same structural entropy as the CCLC for the corresponding slot in simulation group 1. As Figure 4b shows, there was \(\overline{M}_{k}\in\mathcal{S}\) from slot 2 to slot 24, and consequently, these CCLCs were selected using the first method of Algorithm 2. There was a downtrend in the structural entropies of these CCLCs. As more and more CLCs are selected over time and they cannot be selected anymore, CCLCs become less available. There was even one CCLC in \(\mathcal{M^{\prime}}_{k}\) that was obtained by line 8 of Algorithm 2, and its structural entropy was minimal.  
There was \(\mathcal{M^{\prime}}_{k}=\varnothing\) from slot 25 to slot 40, during which CCLCs were selected using the second method of Algorithm 2. Under the circumstance, the structural entropy could not be used as a selection criterion so the structural entropies of these CCLCs fluctuated within a wider range.  
There were 300 ISLs established during 20 slots in simulation group 1 and 412 ISLs established during 40 slots in simulation group 3. The general degrees and the numbers of potential link objects of all satellites are shown in Figure 6. In simulation group 1, every satellite's general degree equaled the number of slots. In simulation group 3, there were 28 satellites whose difference between numbers of potential link objects and general degree was zero, with 2 satellites whose difference was 1. Obviously, our method fully exploited ISL resources to construct an ICNS.