# Multi-Device to Multi-Device (MD2 MD) Content-Centric Networking Based on Multi-RAT Device
## 4 Performance Evaluation and Analysis
### Result of Performance Evaluation  
To evaluate the performance of the existing and proposed methods, an experiment was performed to analyze the connections between devices. A change in the number of devices and the ratio of the number of devices satisfying the user requirements, relative to the total number of devices, was found to affect the performance. First, based on a probability, the average number of connection attempts was obtained for each circumstance. Then, after obtaining the average length of time consumed by repetitively measuring the actual consumed time for each process, the average consumed time was substituted into the formula for obtaining the length of time consumed for each circumstance. Consequently, the connection time was obtained for both the existing method and the proposed method. The changes in the ratio of the number of devices satisfying the user requirements to the total number of devices, and the changes in the total number of devices, are shown in Figure 13. Figure 13 is a graph showing the number of connection attempts according to the ratio change when the total number of devices was assumed to be 10. As the proportion of devices satisfying the user requirements increases, the average number of connection attempts increases exponentially. \begin{table}
\begin{tabular}{c c} \hline
**Component** & **Description** \\ \hline \multirow{4}{*}{Raspberry Pi 2} & Raspbian (Linux kernel 3.18.10) \\  & Hostapd \\  & isc-dhcp-server \\  & BlueZ \\  & CCNx 0.8.2 \\  & USB Dongle \\  & 2.4 GHz \\  & USB Dongle \\  & Bluetooth 4.0 \\ \hline \end{tabular}
\end{table} 
Table 1: Equipment for testbed configuration. Figure 12: Architecture of testbed for performance evaluation. Figure 14 is a graph showing the increases in the total number of devices when the ratio of the number of devices satisfying the user requirements to the total number of devices is 1:1. The rate of increase was large when the total number of devices was small. Because the ratio was consistent, as the total number of devices increased, the rate of increase became smaller and smaller and ultimately converged to a certain value. As shown in Table 2, the actual length of time consumed by each process on the testbed was measured. The average length of time consumed by each process was obtained by repeating each process 200 times: the AP scan time was about 1582 ms; the Bluetooth Beacon scan preparation time was about 152 ms; the Bluetooth Beacon signal scan time was about 148 ms per signal; the AP connection time was about 450 ms; and the AP disconnection time was about 95 ms. The AP or Beacon scan time may vary according to the measurement environment. However, the difference was small. \begin{table}
\begin{tabular}{c c} \hline \hline
**Process** & **Time** \\ \hline AP Scan & 1582 ms \\ AP Connection & 450 ms \\ AP Disconnection & 108 ms \\ Bluetooth Beacon Init & 152 ms \\ Bluetooth Beacon Scan & 148 ms \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Measured lengths of time consumed by each process. Figure 13: Average number of connection attempts according to ratio change. Based on the average number of connections and measured length of time, the results obtained through the equation defining the average connection time for the existing and proposed methods, as well as the results obtained through actual experiment, are shown in Figures 15 and 16. With the existing method, a difference could be observed between the experimental and theoretical values, despite many repetitions. Furthermore, because the value that changes based on the number of connection attempts is large, it can have a major effect on the probability. However, with the proposed method, an experimental value similar to the theoretical value was obtained because the value changed when there was only a small number of receiving Beacons, which was a value that could change through probability.