# Performance Evaluation of IEEE 802.11 ah Networks With High-Throughput Bidirectional Traffic
## 4 Performance Evaluation and Discussion
### Reliable Monitoring Scenario
#### 4.3.2 Reliable Monitoring: Results  
Figure 8 shows, for different sensor sampling rates, the maximum number of stations that can be supported for different combinations of the number of TIM groups and RAW slots. Intuitively, achievable density generally does not decrease when decreasing sampling rates (decreasing overall traffic load) as shown in Figure 8. For the smallest evaluated sampling interval (10 s), the use of 16 TIM groups already introduces too much latency, leading to a rapidly decreasing maximum attainable density. However, the highest density is generally achieved for many TIM groups and a few RAW slots. At least 1500, 3200, 3800, 4960, 6120 and 6960 stations can reliably report every 10, 20, 30, 40, 50 and 60 s, respectively, with no packet loss. Consequently, there is a trade-off between achievable density and traffic load. IEEE 802.11 ah can support thousands of stations as long as each of them has limited traffic demands. In that manner, the relation between attainable density and sampling interval is almost linear as shown in Figure 9. Increasing the number of RAW slots limits the available channel time and thus limits the scalability. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameter** & \multicolumn{5}{c}{**Values**} \\ \hline Traffic interval (s) & 10 & 20 & 30 & 40 & 60 & \\ Contention per RAW slot & 9 & 14 & 19 & 24 &... & 999 \\ \(N_{TIM}\) & 1 & 2 & 4 & 8 & 12 & 16 \\ \(N_{RAW}\) & 1 & 2 & 5 & 10 & & \\ Payload size (bytes) & 100 & 200 * & 300 * & 400 * & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Configuration parameters for the reliable monitoring scenario. High payload sizes (marked with *) have only been evaluated with 8, 12 and 16 TIM groups. Figure 8: The highest density without any packet loss is achieved with high number of TIM groups and low number of RAW slots, depending on sampling rate (traffic load). (**a**) \(T_{s}=10\) s; (**b**) \(T_{s}=20\) s; (**c**) \(T_{s}=40\) s; (**d**) \(T_{s}=60\) s.  
RAW slotting is beneficial for reducing contention; however, it can be limiting if bidirectional traffic is present as it postpones transmissions for paged stations. Hence, reliable bidirectional communication among 6880 stations with a sampling interval of 60 s and 16 TIM groups is possible for 1 and 2 RAW slots, whereas for 10 slots it is only possible only among 4800 stations. Multiplying the sampling interval and payload size by the same factor is beneficial for the overall scalability. While the overall reception rate at the server will remain the same, the maximum density rises considerably by grouping \(n\) measurements together and reporting them less frequently (every \(n\cdot 10\) s) as shown in Figure 10. A larger packet size makes better use of the available channel time: it reduces the overhead of the headers, the amount of TCP acknowledgements and the number of collisions. For five RAW slots, grouping two measurements together and reporting them twice less frequently enables support for twice as many stations. For two RAW slots, this difference is somewhat smaller but grouping up to 3100-byte measurements together and reporting them up to three times less frequently enables an additional 1120 stations. We tested grouping up to four measurements, since any larger values would result in exceeding the 536 bytes TCP segment size and would cause more traffic due to IP fragmentation. On the other hand, increasing the packet size makes the use of configurations with a large number of short slots impossible, due to infeasibility to transmit (receive) large packets in too short slots as discussed in Section 4.4. The possibility of grouping measurements together and reporting them less frequently greatly depends on real-world application. In delay-intolerant systems, this might not be possible; however, it is greatly beneficial for scalability when possible. Increasing the number of TIM groups instead improves scalability but also increases latency considerably (Figure 11) and RTT even more.