## 4 Performance Evaluation
### Evaluation of MRSS-based Handoff Algorithm
\begin{table}
\begin{tabular}{|l|c|c|c|c|c|c|c|c|c|} \hline Handoff method & MRSS & MRSS & DMRSS & MACD & T & T + D & T + H + D & T + H & G \\ \hline \(\alpha\) & 0.29 & 0.5 & 0.29/0.5 & 0.29 & — & — & — & — & — \\ \hline \(\beta\) & — & — & — & 0.04 & — & — & — & — & — \\ \hline \(k\) & 16 & 8 & 16/8 & 16/256 * & — & — & — & — & — \\ \hline \(TH_{P}\) (dBm) & 1 & 1 & 1 & 1 & — & — & — & — & — \\ \hline \(TH_{N}\) (dBm) & -1 & -1 & -1 & -1 & — & — & — & — & — \\ \hline \(TH_{ND}\) (dBm) in WLAN & -92 & -92 & -92 & -92 & -92 & -92 & -92 & -92 & — \\ \hline \(TH_{HO}\) (dBm) in WLAN & -98 & -98 & -98 & -98 & -98 & -98 & -98 & -98 & — \\ \hline \(TH_{ND}\) (dBm) in WiMAX & -92 & -92 & -92 & -92 & -92 & -92 & -92 & -92 & — \\ \hline \(TH_{HO}\) (dBm) in WiMAX & -95 & -95 & -95 & -95 & -95 & -95 & -95 & — \\ \hline \(TH_{Dwell}\) (s) & 2 & 2 & 2 & — & — & 4 & 4 & — & — \\ \hline Hysteresis (dBm) & — & — & — & — & — & — & 10 & 10 & — \\ \hline \end{tabular}
\end{table} 
Table 7: Parameters for the evaluation of handoff mechanisms in WLAN and Mobile WiMAX. MN executes handoff. Unnecessary handoffs may decrease the transmission performance and the quality of the applications. * **Number of failure handoff**: A handoff may fail if an MN starts the handoff procedure too late. Moreover, fading may cause the variation of RSS and lead to unnecessary handoffs. It may increase the risk of broken connection due to handoff failure and damage the performance of applications. The performance evaluation results of various handoff algorithms in the mobile WiMAX environment are shown in Figures 15(a)-15(d). Figure 15(a) illustrates the average motion detection delay of MACD, MRSS and dynamic MRSS. In Figure 15(a), MACD has the largest motion detection delay because it is less sensitive than MRSS. The MRSS with a larger smooth factor \((\alpha)\) can detect the user motion faster than the MRSS with a small smooth factor. Using a larger \(\alpha\) in MRSS can speed the response to the change of RSS, which results in fast motion detection but also unnecessary handoffs. When the RSS of an MN is lower than the predefined network discovery threshold \((TH_{ND})\) and the MN moves toward the edge of the cell in a short distance then stops, the MRSS algorithm always triggers network discovery and makes a handoff because it can quickly predict the leaving state. On the other hand, MRSS with a small \(\alpha\) results in a high motion detection delay. Thus, using a dynamic smooth factor is a better approach. Figure 15(b) shows the accumulated active time of all interfaces in various approaches. In Figure 15(b), the traditional RSS threshold-based methods consume more power than motion detection-based handoff approaches. In the RSS threshold-based handoff method and the hysteresis combined methods, an MN turns on all interfaces to search for available access networks and executes handoff procedure only according to \(TH_{ND}\), \(TH_{HO}\) and hysteresis. In addition, the dwell time methods require an MN to remain in the network discovery mode over the dwell time. Thus, these methods consume more power than the motion detection-based approaches. Moreover, the MRSS-based handoff method can identify the user motion state quickly. The MRSS with a larger \(\alpha\) can detect the user motion state faster than the MRSS with a small \(\alpha\), MACD and dynamic MRSS. Figure 15(c) illustrates the accumulated number of handoff. In Figure 15(c), the geographic-based handoff method has the lowest number of handoff because it triggers the handoff process according to the GPS information. The RSS threshold based handoff algorithm causes the largest number of handoff because the MN always triggers handoffs even when the MN is in a stationary state. The dwell time combined methods and the hysteresis combined methods limit the handoff trigger by a dwell time constraint and a hysteresis constraint, thus the MN triggers handoff late and makes a slightly lower number of handoff than that of the motion detection based handoff algorithm.