## 4 Performance Analysis and Discussion  
### Latency Measurement  
The work and instructions issued by the ATCOs indirectly affect the safety of the flight crews and passengers on board. As pilots need some time to execute the instruction from the ATCOs, the response time of humans should be considered during decision making. In addition, aircraft are usually travelling at a high speed; thus, consequences might still occur even when correct decisions are made. If the decisions are delayed, the consequences might be hard to reverse. Therefore, despite it being essential to make error-free decisions, timely decisions should also be made. Hence, the decisions should be supported by instantaneous/near-real-time data to ensure validity. Given this, the latency of the data transmission process should be adopted to evaluate the performance, especially if the network is wireless. Figure 7 shows the method utilised to measure the latency of the system. As the data transmission process is mainly conducted through _SimConnect_, it is more appropriate to snapshot the time of data request at the client side instead of the time of request arriving at the server. This can be accurately timestamped in the data request application, and it is denoted as \"Timestamp 1\". The second timestamp snapshotted is when the data are received by W-ATCOs, denoted as \"Timestamp 2\". Therefore, the difference between \"Timestamp 1\" and \"Timestamp 2\" is the time elapsed for data request and data return transmission through the wireless network. As the ATCOs only read the radar map instead of directly interpreting the raw data, it is essential to have the third timestamp snapshotted. Moreover, it is crucial to evaluate the time elapsed between data reception and data visualisation. \"Timestamp 3\" is the time that the data is visualised in the radar map. Hence, the elapsed time from \"Timestamp 1\" to \"Timestamp 3\" is the total time used to complete one request, while that from \"Timestamp 2\" to \"Timestamp 3\" is the time spent on the flight parameter passing procedure and visualisation. Tables 2 and 3 show a summary of the timestamps selected for latency measurement and the key performance indicators (KPIs) of the system's latency, respectively. Figure 7: The measurement of latency. The KPIs are the latency performance indicators defined by the time difference between every two timestamps that are recorded. The experimental evaluation was conducted using the platform described in Section 3.1. The evaluation was done using a flight task consisting of the three major flight phases, classified as take-off and climbing, en route cruising (with autopilot enabled), and descent and landing. It is expected that the traffic density in the flight simulator will affect the computational performance, and hence result in latency. Therefore, for each flight phase, an experiment was designed and implemented for different traffic densities, i.e., light traffic load at 10%, medium traffic load at 50%, and heavy traffic load at 100%. The light traffic load was set to 10% instead of 0% as having 0% air traffic density is unrealistic. The entire flight task lasts around 60 min from Hong Kong International Airport to Kaohsiung Siaogang International Airport. Furthermore, the difference in graphics between daytime environment and night-time environment can affect the latency. Therefore, the time setting, i.e., day (10:00 a.m. local time, start time of the flight) and night (8:00 p.m. local time, start time of the flight) in the flight simulator was another independent variable in the experiment. A trial of the flight task was conducted for each experimental setting, i.e., each set of independent variables. The acceptance criterion of satisfactory performance was 500 ms (one-way) as suggested by [PERSON], et al. [34] for ADS-B-Out message transmission.