## 6 Simulations and Discussion  
In the previous section, a detailed Markov model and related calculations are given. In order to validate the proposed model, an OPNET-based simulation is carried out here. We mainly focus on several major parameters of the network, including the throughput, packet delay and packet discard probability. With the simulation and analytical results, the performance of the on-board network is evaluated. A star topology network is established, in which one node is set as the host node and the others slave nodes, and only single-hop communication is involved. According to our design experience and that of other research groups [31; 46], in every sampling period, the data size of a typical on-board subsystem is around 60-70 bytes. Thus, their data packet is set to 80 bytes (need 1.28 ms). The length of the superframe is 200 ms and it is divided into 100 slots (includes 3 beacons). Therefore, the length of each slot is 1.6 ms and the gap between the slots is 0.4 ms. The TDMA period contains 40 slots. We assume that there are 40 nodes in this period, which means every node receives one scheduled slot in this period. While in the CSMA period, the nodesnumber varies from 5 to 30, and its length is up to 57 slots. Several default values of the parameters are specified in the simulation as \(m=4\), \(BE=4\) and \(NB=2\). Figure 12 shows the variation of throughput with respect to packet arrive rate \(\lambda\) and network size. With the increase of \(\lambda\), the network throughput increases until it reaches the maximum. The growing \(\lambda\) then causes more frequent collisions and the throughput consequentially falls with it. For different network sizes, the larger networks have a higher throughput in small \(\lambda\) and they reach their maximums faster. However, since larger networks suffer more from collisions, their throughputs are declining more rapidly, too. Figure 13a shows the variation of average packet delay with BE. The packet arrival rate is set to 0.01 per slot. With the growth of the network scale, the average packet delay increases too. Further, networks with smaller BE have better delay performance. However, as shown in Figure 13b, for a large-scale network, a lager BE relieves the collision and performs better in throughput. Therefore, when there are few nodes in the network, it is more appreciate to choose a small BE since the collisions happen in a low probability. In addition, a long backoff window will lead to unnecessary time consumption and jeopardize both the packet delay and network throughput. On the other hand, for a large-scale network, a long backoff window helps to relieve the collisions and achieves higher throughput. Figure 12: Cooperation of throughput for different network size. Figure 13: The variation of packet delay and throughput with nodes number for different BE value. (**a**) Average packet delay; (**b**) Network throughput. The maximum number of retransmission (\(R\)) is set to 3. If a data frame has been retransmitted for 3 times, then it will be directly discarded. As shown in Figure 14a, it is clear that a lager m will effectively reduce the packet discard probability. A larger _macMaxCSMA_ value indicates that more backoff processes are performed and it leads to a lower transmission failure rate. At the same time, as shown in Figure 14b, when the network has very few nodes, the network performs higher throughput with a smaller \(m\). With the increase of the network scale, a larger m assists to relieve collisions and achieve higher network throughput. Since the packet discard probability and the throughput are influenced differently by the _macMaxCSMA_, both the network size and performances requirements should be considered when selecting a suitable _macMaxCSMA_ value. As shown in Figure 15a, the one CCA strategy adopted in this article obtains higher throughput than the standard two CCA strategies.