# Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks
## 4 Results and Discussion  
### Simulation Scenarios and Evaluation  
In WSNs with cluster-based routing [55; 56; 57], the shorter the distance separating the sink from the CH is, the more the power is conserved, and the lower the packet collection latency is. Using numerous sinks to replace a single sink can significantly decrease these distances. Using multiple sinks, every cluster head can communicate with the nearest sink. Therefore, it is possible to enhance the QoS performances by deploying multiple sinks [58] or relay nodes [59; 60] to gather sub-regional data. This technique has been proven effective in reducing distances and improving overall performance. Hence, it is a preferred solution for achieving a better quality of service performance. As a result, the primary sensor network is partitioned into smaller networks with a low diameter. These sub-networks consist of sensors and a static or mobile sink, forming a cluster. Cluster heads transfer information to the respective sink of the corresponding sub-region. The study's initial scenario will focus on a simulation of a field measuring 400 m \(\times\) 400 m, hosting eight hundred nodes with random positions. This used static sink is situated beyond the RoI. Further, the simulation will be repeated four times using a mobile sink, which follows one of the four designated mobility models in Figure 2a. Another scenario implies the same RoI and number of nodes, but the sensing field is split into two 400 m \(\times\) 200 m sections. Each half will be controlled, once with a static sink positioned beyond the supervised RoI, and four times with a mobile sink that follows one of the four mobility models, so we will have two fixed sinks and two mobile sinks, as illustrated in Figure 2b in the third scenario, it is the same principle as the second scenario except that we divide the main field into four subfields sized of 200 m \(\times\) 100 m. In this case, we will have four fixed and four mobile sinks, as illustrated in Figure 2c. Finally, for the fourth scenario, we also keep the same principle as the other scenarios, but this time, we divide the initial field into eight subfields of 200 m \(\times\) 100 m. In this case, we will have eight static and eight mobile sinks, as shown in Figure 2d. The assessment analysis of the introduced system relies on various assumptions, including the supposed stationary state of all deployed sensor nodes, coupled with their location awareness. The utilization of a cluster-based routing protocol has also been considered, where only CHs are authorized to transfer gathered information to the designated sink. The latter changes its position through the network following a designated mobility model that facilitates data collection from the respective cluster heads. Each sensor node uniformly issues a standard amount of data per unit of time (i.e., one packet per second) with an equivalent data length of 100 bytes. The energy of transmission of each sensor is adapted to the adjacent nodes' relative distances. The mobile sink is supposed to hold enough power reserves to communicate and relocate at any point within the network. The static base stations in each scenario are positioned 20 m beyond the field margins. According to the operating principles of the three hierarchical protocols described above, an election phase is planned each period (i.e., 20 s for LEACH) to choose a new CH. Additionally, all sensor nodes have identical communication capacity and computing resources. Table 2 highlights the relevant, considered parameters. The metrics chosen for evaluation are as follows:  
* Energy consumption (The consumed energy by all the sensor nodes)
* Throughput (Total data collected by sink)
* Data delivery rate (Reliability)