# A Semantic and Knowledge-Based Approach for Handover Management
## 4 Evaluation
### Results and Analysis  
Table 3 shows that SIM-Know and AHP-TOPSIS outperformed SSF, in terms of the number of handovers and the number of throughput drops, when the end-user device moved at any speed (slow, moderate, or high). This behavior is expected because SSF is the baseline and triggers a handover as soon as an AP with an RSSI higher than that of the serving AP is available. Table 3 also reveals that when the end-user device moved at slow and moderate speeds, SIM-Know behaved as AHP-TOPSIS does regarding the number of handovers and the number of throughput drops. Figure 7 shows that SIM-Know outperformed AHP-TOPSIS in these metrics when the end-user device moved at a high velocity. The outperformance regarding the number of handovers and number of throughput drops was due to SIM-Know making context-aware, cognitive and proactive handovers. Figure 8 corroborates the fact that SIM-Know carried out handovers before SSF and AHP-TOPSIS did. Figure 9 shows, as expected, that SIM-Know obtained a higher handover latency than SSF did, since our approach is knowledge-based and SSF makes decisions considering a \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **SSF** & **AHP-TOPSIS** & **SIM-Know** \\ \hline \hline \multicolumn{4}{c}{**SlowMobility**} \\ \hline Number of handovers & 7 & 3 & 3 \\ \hline Number of throughput drops & 5 & 3 & 3 \\ \hline \multicolumn{4}{c}{**ModerateMobility**} \\ \hline Number of handovers & 7 & 3 & 3 \\ \hline Number of throughput drops & 5 & 3 & 3 \\ \hline \multicolumn{4}{c}{**HighMobility**} \\ \hline Number of handovers & 7 & 4 & 3 \\ \hline Number of throughput drops & 5 & 2 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Handover Performance. Figure 7: Throughput Drops. single criterion. SIM-Know had 27% less handover latency than AHP-TOPSIS because, first, our approach is proactive and, according to [46], AHP-TOPSIS is reactive; the proactivity shortens the Handover Initiation phase [21]. Secondly, SIM-Know employs a rule-based reasoning method while AHP-TOPSIS uses a complex mathematical model that requires a considerable amount of time to make handover decisions. Next, we present how SIM-Know, SSF and AHP-TOPSIS impact various network performance metrics when the end-user device moves at _HighMobility_. Figure 10 depicts SIM-Know overcoming SSF and AHP-TOPSIS regarding the throughput, delay, and packet loss when the wireless network transferred VoIP/UDP traffic. In particular, the delay attained by SIM-Know was 29.28% and 23.13% lower than that achieved by SSF and AHP-TOPSIS (see Figure 10a). The packet loss of SIM-Know was 99.44% and 98.38% lower than that obtained by SSF and AHP-TOPSIS (see Figure 10b). The throughput obtained by SIM-Know was 57.17% and 16.87% higher than that obtained by SSF and AHP-TOPSIS (see Figure 10c). Figure 11 shows that SIM-Know also outperformed SSF and AHP-TOPSIS regarding the throughput, delay and jitter when the wireless network transferred TCP traffic. Specifically, the delay attained by SIM-Know was 91.95% and 80.27% lower than that achieved by SSF and AHP-TOPSIS (see Figure 11a). The jitter performed by SIM-Know was 57.98% and 32.94% lower than that obtained by SSF and AHP-TOPSIS (see Figure 11b). The  
Figure 8: Proactivity. Figure 9: Handover Latency. throughput accomplished by SIM-Know was 80.3% and 29.22% higher than that attained by SSF and AHP-TOPSIS (see Figure 10(c)). We argue that the improvement in throughput, delay, jitter, and packet loss offered by SIM-Know is due to its context-aware, cognition and proactivity capabilities, which decreased the number of handovers and the number of throughput drops. In particular, SIM provides the context-aware capability to perform handover decisions through the comprehensive and semantic network view given by the information domains (_Network_, _Application_, _User_, _UserDevice_, and _Handover_). The KBP's _Reasoning_ layer allows the achievement of cognitive HM.