# An Adaptive Hierarchical Hybrid Multicast Based on Information-Centric Networking
## 5 Evaluation
### Control Overhead  
Firstly, we evaluated the control overhead of AHHM and BIER. Control overhead refers to the number of destinations that the router needs to track and maintain in the stateless mode. We counted the maximum number of destinations tracked among all routers, and the experimental results are shown in Figure 8.  
Figure 8a shows that the control overhead in AHHM gradually decreases as the threshold increases. This is because AHHM prefers to use the stateful mode. When the threshold is increased, more groups use the stateful mode to establish multicast communication, thereby greatly reducing the control overhead of the router. Figure 8b,c shows that the control overhead in both AHHM and BIER increases with the number of receivers and groups. Figure 8d shows the CDF of the control overhead in each multicast approach. Compared with BIER multicast, AHHM can significantly reduce the number of destinations tracked and maintained by each router.  
By analyzing the experimental data, we can find that the AHHM using the nearest selection strategy reduces the control overhead by 67.2% on average compared to the BIER. In BIER, the ingress router needs to track the information of all egress routers at the receiver-side for each group. In AHHM, only the information of RERs on stateless sub trees needs to be tracked, and the information of RERs that need to be maintained is balanced on root nodes of multiple stateless sub trees, not only on the SER.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Value** & **Parameter** & **Value** \\ \hline Topology Model & Router Waxman & \(\alpha\) & \(1/3\) \\ Node Number & 200 & \(\beta\) & \(1/3\) \\ Edge Number & 800 & \(\gamma\) & \(1/3\) \\ Node Placement & Random & \(D_{max}\) (hops) & 5 \\ Bandwidth Distribution & Constant & \(S_{max}\) (states) & 200 \\ m (Number of links per new node) & 4 & \(T_{max}\) (flows) & 200 \\ Bit String Length (bits) & 2 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Evaluation settings.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Set Number of** & **Threshold** & **Group Number** & **Receiver Number** \\ \hline
1 & 20, 40, 60, 80, 100 & 200 & 20 \\
2 & 20 & 200 & 10, 20, 30, 40, 50 \\
3 & 20 & 50, 100, 150, 200, 250, & 20 \\
4 & 20 & 300 & 20 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters of each set of experiments.  
In addition, we can also find that the minimum cost selection strategy reduces the control overhead by 40.6% on average compared with the nearest selection strategy in AHHM. When establishing multicast communication from the MJN to the receiver, AHHM preferentially uses stateful mode and switches to the stateless mode when encountering the router whose NFT load reaches the threshold. Unlike the nearest selection strategy, which only considers the factor of distance, the minimum cost selection strategy comprehensively considers the factors of distance, node status, and link status. Therefore, the minimum cost selection strategy can use the low-load nodes and links to establish the multicast communication from the MJN to the receiver in the stateful mode, thereby reducing the RER information that needs to be maintained.