## 4 Extended Simulation Analysis  
The simulation analysis presented in this section intends to validate one of DSSRCA's features, which is the fact that it uses only one radio for communication. Therefore, the experiment simulates a UAV acting as mobile data collector (MDC), which collects data from a WSN and then forwards it to a Sink node. It considers a practical example of an environmental monitoring system where sensors, organized into non-overlapping clusters, are deployed in a remote area. The sensor nodes sense their environment and save data in their buffers. Each sensor transmits data to its corresponding cluster head (CH), which in turn saves it and eventually send it to the UAV whenever it is in communication range. The cluster heads are responsible for coordinating the operation of the cluster members and also for communication with  
Figure 11: Data rate in the communication between the Sink and MDC, in a link with 40% loss probability and 50 ms network latency. Figure 12: Simulation scenario: UAV flies over 45 nodes organized into five clusters. the UAV. A simulated environment of this scenario was developed in Omnet++ 4.41 with Inetmanet-2.0. The simulated environment was 1000 m \(\times\) 1000 m. The altitude of UAV was kept constant at 15 m above the ground. We used 45 sensor nodes, organized into five clusters on the basis of distance from each others. Such simulation scenario is depicted in Figure 12.  
To perform this experiment the following reasonable assumptions were made:  
* A Sink node knows the location and propagation model (communication range) of all the ground sensors. * The UAV is equipped with GPS, so that it can calculate its current position. The transmission range of each node, including the CH is approximately a circle with 90 m radius. The radio model used for all nodes including UAV is 802.15.4. The UAV can make use of the extended transmission power (+19 dBm) to send data (telemetry or collected) back to the Sink, while traversing the network area. Before starting data collection, the Sink generates a flight plan for UAV, as it has all the necessary information regarding locations and radio ranges of sensors. The length of each data collection lap is approx. 1650 m. It should be noted that when the UAV starts flying, it already knows what trajectory to follow. The UAV can always estimate the start and end points of each CH zone. It is also assumed that the UAV trajectory passes over the CH node according to the flight plan generated by the Sink. The mechanism of this initial flight plan generation and its optimization is not considered here and is out of the scope of this work. We also do not consider how the sensors within each cluster behaves and communicate with CH. We assume that the sensor nodes remain silent (go into sleep mode) whenever the UAV enters the communication range of a CH. These sensor nodes remain in sleep mode until the UAV goes out of the coverage zone of that particular CH. This helps to avoid message collisions and disturbance in CH-to-UAV communication. This sleep/wake-up coordination is simply achieved by cooperation between UAV and CH. Whenever a UAV is about to enter a CH coverage zone it announces its speed while contacting the CH. Knowing his coverage area, the CH can easily calculate the time, the UAV is about to spend in communication range and instruct the sensors to go to sleep mode for at least that duration. After the generation of the flight plan, the UAV begins traversing the network area and starts collecting data. As the UAV knows the location of each CH, when it enters the communication range of CH1, it asks CH1 to start sending its data. In case, the UAV does not know the location of each CH, a three-way handshake could be used for identifying the underlying CH. In this experiment, the UAV was tested at different speeds, starting from the Sink on a pre-defined path, covering a total distance of 1650 m and returning back to the Sink again.