# FollowMe: One Social Importance-Based Collaborative Scheme in MONs
## 6 Experimental Results and Analysis  
In this paper, we integrate FollowME into the classical routing algorithms PRoPHET and SimBet, and implement it in a custom routing simulation platform based on the Visual C++ 6.0. We evaluate its performance metrics by comparing it with the performance of the random update strategy, which is widely used in recent works [13; 14; 15]. We used two real data sets, KAIST and NCSU [22], and one mobility model SLAW, to test the performance of FollowMe under different network conditions. KAIST is obtained from the Korea Institute of Science and Technology (KAIST) and records the daily activities of the population on campus. A total of 34 people participated in the data collection process, each with a handheld GPS device to collect 92 days movement trajectory. NCSU records the moving traces of 20 students in the campus dormitory area from North Carolina University. The detailed information of the datasets are shown in Table 1.  
This paper uses three metrics to evaluate the performance of routing algorithms: (1) Cooperation Rate (CR): the ratio of the total number of cooperating nodes to the total number of nodes in the network. The higher the cooperation rate, the more nodes in the network are willing to forward messages to other nodes; (2) Packet Delivery Ratio (PDR): the number of data packets to the destination over the total number of packets generated. The higher the PDR, the larger the number of data packets in the network that are successfully delivered to the destination node; (3) Packet Delivery Hops (PDH): the average number of hops required for the data packet to arrive at the destination node from the birth node. The lower the number of hops, the fewer the number of intermediate nodes needed to forward the message, i.e., the lower the demand for network resources. The simulation parameters are as follows: in the prisoner's dilemma game payoff matrix, \(R=1\), \(S=-1\), \(T=1.5\), and \(P=0\). In the Fermi function, the noise coefficient \(n_{0}=0.5\) and the initial cooperation rate of all nodes in the network \(\theta=60\%\). Figure 2 shows the results of CR between FollowMe and Random. We can observe that the cooperation rate is initially similar; however, FollowMe obviously has a higher CR than Random with the simulation process. Moreover, as the time increases, FollowMe still maintains a high CR while the Random strategy fails to drive nodes. This is mainly because FollowME takes the social importance of nodes into account and use it as a signal to motivate nodes to cooperate. On the contrary, the Random solution just takes the action from one of neighbors as a reference, and the selected neighbors maybe a node with lowly social importance, which has little help to forward packets. The cliff point in the initial stage of the random algorithm is because the random update strategy does not consider the imitation behavior between nodes, and all nodes tend not to forward data (the most benefit when not forwarding). Therefore, in order to maximize the benefits of each node, each node achieves a stable state in a short period of time, but the cooperation rate is low. \begin{table}
\begin{tabular}{c c} \hline \hline
**Simulation Field Size** & **600 \(\times\) 600 m\({}^{2}\)** \\ \hline Simulation time (KAIST/NCSU/SLAW) & 15,000 s/15,000 s/18,000 s \\ Number of nodes (KAIST/NCSU/SLAW) & 90/35/500 \\ Communication range & 15 m \\ Node storage size & 20 MB \\ Message size & [0.5, 1] MB \\ The TTL of the message & 300 s \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation parameters. Figures 3 and 4 evaluate the PDR performance of FollowMe in PRoPHET and SimBet, respectively. Clearly, the PDR of FollowMe is almost twice as high than that of Random during the entire simulation. This is mainly because the CR of FollowMe is higher than that of Random, which means more nodes are willing to assist other nodes to relay data packets. Hence, additional data packets can be relayed, increasing the probability of contact with the destination and improving the PDR slightly.