# Impact of Latency on QoE, Performance, and Collaboration in Interactive Multi-User Virtual Reality
## 4 Results and Discussion
### Objective System Performance
However, while on the server-side outgoing traffic is blocked before transmission, this behavior is not observed on the downlink. Also notice that the high throughput peaks (up to 1.2 Mbps) at computationally heavy moments of the experience with a lot of synchronization messages (e.g., sauce spreading), which, given the network constraints, results in a high number of re-transmissions as well. Figure 8 shows the latency distributions for each link in each of the four network configurations. In Figure 8a, the distributions of the unconstrained system are shown, indicating average latency of 11.3 ms and 12.6 ms for downlink and uplink, respectively. In addition, the spread in the uplink is shown to be somewhat larger than is the case for the downlink. Similar behavior can be observed for scenario B (Figure 8b), albeit with a larger spread of the distribution on the downlink. This is because every packet has a 50% chance of being blocked for 500 ms at the server before effectively being sent due to the burst implementation. A lot of these packets will be effectively resent within 500 ms (as each re-transmission has an equal 50% change of not being blocked), therefore resulting in a limited increase in the average latency. For a limited portion of the packets though, no successful re-transmission will take place within this interval, therefore effectively resulting in a 500 ms latency, causing the distribution to stretch. Furthermore, this also explains the positive skewness in the data, which can be noticed from the difference between the median and the average. As the uplink packets are only blocked on entering the server, this phenomenon is not observed here. Scenario C (Figure 8c) shows similar behavior  
Figure 7: Evolution of the obtained throughput over time, for each link and each network configuration, of a randomly selected session. Note the different y-scale of configuration A for readability. as scenario A, albeit shifted with the artificially added 500 ms of latency. In addition, an increased spread and positive skewness of the downlink distribution can once again be observed due to re-transmissions in the traffic. For scenario D (Figure 8d), rather binary behavior is observed. For the uplink, one can notice a similar distribution as in scenario C. On the downlink, however, a much wider and skewed distribution can be seen, with a median of 1002.0 ms and an average of 786.1 ms. This is because the combination of the 500 ms burst and latency in one system shapes the latency in a bi-modal distribution, as can be seen from Figure 9. In contrast to scenario B, none of the re-transmissions resulting from the 50% blocking chance will arrive in time, as every packet by default experiences a 500 ms latency. As such, around half of the packets will not be affected due to the burst, resulting in \(\pm\)500 ms latency, while the other half suffers from an additional 500 ms delay due to the burst. As such, the latter totals to a latency of around 1000 ms, therefore effectively creating two distinct modes in the distribution. Due to the server-side implementation of burst, as explained before, this behavior is not observed on the uplink. Figure 8: Distributions of the measured latency, over all playthroughs, for each link and each network configuration. The full orange line indicates the median, the green dotted line the mean. Figure 9: Histogram illustrating the bimodal nature of the latency distribution on the downlink in configuration D.