## 8 Simulation Environment  
This section shows and discusses the detailed explanation of the tests. In NS2 we ran our experiment for 30-min online live packet streaming of UDP packets. UDP packets are good examples of video live streaming packet transmission. m-QoS is optimized in the source point and starts to be calculated during healthcare video transmission at the remote location. Here, we assume a media stream with high un-stability, such as loss of the connection during surgery of emergency patients, which causes more delay and  
Figure 5: Sending receiving emergency packets. will be risky to his life. A comparison of QoS optimization is shown for proposed wRCA and s-RCA, rerouting normal packets if the booking node receives, other than emergency packets, using the configuration parameters displayed in Table 1. Experimental results of performance analysis in Table 1, reveal that window-based rate control algorithm (w-RCA), s-RCA, and re-routing normal packets depend on various buffer sizes and start-up delays (0 t of 2 frames). It was observed that increased idle time decreases the media sequence's rate variability. Surgery simulation is conducted for attending a 99% confidence level in the outcome (detailed parameters are presented in Table 1. As discussed above, we compare w-RCA with another existing work. The experiment is performed by taking into account the client buffer size, our new technique (s-RCA), and rerouting normal packets, to prove that our technique will not affect the networks during the surgery time. For QoS optimization in terms of different QoS metrics (such as packet received ratio and delay over 5G network), we establish a trade-off between packet size and buffer size, with reducing packet loss ratio, which shows the smooth peak-to-mean ratio, less delay, and less jitters. The analysis is based on packet size transmission of the real-time video buffer rate (VBR) for medical video quality. To evaluate the performance of the s-RCA algorithm in the IoT environment, we modeled a different type of mesh topology scenario in NS2. Each scenario had a different number of nodes. We also considered the amount of traffic that could be passed on the network in each experiment. The topology started from 50 up to 200 nodes: the node at the beginning of the network acted as the source node, while the one at the end of the network alternately generated one normal data packet and one urgent data packet, within a period of seconds. Network simulation (NS2) was performed to evaluate the performance of the proposed long VPN path between the source and the destination in terms of receiving high-priority traffic for medical operations or any other important high-emergency traffic involving the on-demand protocol between nodes in networks. The evidence gathered by the NS2 simulation offered good support for the transmission data in the networks. We repeat our simulation around 30 times and we have taken the average delay among all of them. The packet size was 100 B and the bit rate was set to 2 MB/s. A traffic rate of 200 KB/s was generated from the source node to the destination during simulation. Before evaluating the performance issues for the network topology, it is important to determine which parameters could affect the QoS of the streamed video traffic. Here, the research focuses on three parameters, which may better determine the effect of video traffic techniques:  
* Packet loss ratio: this is the packet ratio between dropped and sent data packets. * Average delay time in the buffer: this is the average time between transmission and arrival data packets include the buffering time. * Throughput as we checked how many packets were received during the path booking and if there are some packets dropped do they will make a huge problem for doing the required task. However, we have created an extension to the routing protocol by performing our Algorithm 1 in order to prepare an adjacent node to be the next hop if faced with the required conditions.