## 4 Simulation and Results  
### Simulation Parameters and Setup  
To evaluate the performance of the proposed algorithm, we consider two scenarios with simulation parameters outlined in Table 1. The simulation involves a network area of 200 m\({}^{2}\) network area, where two different BS locations are examined: Scenario 1 places the BS at (100 m, 300 m), while Scenario 2 positions it at (100 m, 100 m). Within this area, 100 sensor nodes are deployed, each node beginning with an initial energy (\(E_{init}\)) allocation of 0.5 \(J\).  
Figure 2 illustrates the simulation setup within a 200 m\({}^{2}\) network area for evaluating the impact of mobility and clustering protocols under varying BS locations. The network comprises distributed sensor nodes (both CH and non-CH nodes), a BS, and an autonomous vehicle equipped with a sensor node. Two scenarios are considered to analyze the influence of the BS location and node mobility on the performance of clustering algorithms. In Scenario 1, the BS is positioned at (100 m, 300 m), creating a distant BS placement that highlights the energy efficiency of clustering protocols under higher communication costs. In Scenario 2, the BS is relocated closer to the nodes at (100 m, 100 m), reducing communication overhead and emphasizing the effects of mobility within the cluster. This setup evaluates the performance of mobility-aware clustering protocols under realistic WSN conditions, assessing their adaptability to node mobility, cluster stability, and energy efficiency while highlighting the impact of mobility on the network lifetime.  
The energy parameters set for the simulation include 10 \(pJ\) per bit per m\({}^{2}\) (\(e_{fs}\)) for free space transmission and 0.0013 \(pJ\) per bit per m\({}^{4}\) (\(e_{mp}\)) for multipath transmission. The hardware of these sensors requires 50 \(nJ\) of energy per bit for transmission and reception processes (\(E_{T}\) and \(E_{R}\), respectively). Additionally, data aggregation demands an energy expenditure of 5 \(nJ\) per bit (\(E_{DA}\)). Communication within the network utilizes a message size (\(l\)) of 5000 bits per message. The maximum mobility range is assumed to be within 10 m per round in the simulation. In real-world scenarios, mobility is typically expressed as speed in meters per second (m/s), which may vary depending on the specific application.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Simulation Parameter** & **Values** \\ \hline Network Area, \(M\) & 200 \(\times\) 200 m \\ Position of the BS & Scenario 1: (100 m, 300 m) \\ Scenario 2: (100 m, 100 m) \\ Number of Sensor Nodes, \(N\) & 100 \\ Initial Energy of Sensor Node, \(E_{init}\) & 0.5 J \\ Number of Rounds & 2000 \\ Radio Amplifier Energy Coefficient for Free Space & 10 pJ/bit/m\({}^{2}\) \\ Transmission, \(e_{fs}\) & 10 pJ/bit/m\({}^{2}\) \\ Radio Amplifier Energy Coefficient for Multipath & 0.0013 pJ/bit/m\({}^{4}\) \\ Transmission, \(e_{mp}\) & 50 nJ/bit \\ Receiving Energy per Data Bit, \(E_{T}\) & 50 nJ/bit \\ Transmitting Energy per Data Bit, \(E_{R}\) & 50 nJ/bit \\ Energy Required for Data Aggregation, \(E_{DA}\) & 5 nJ/bit \\ Message Size, \(l\) & 5000 bits/message \\ Maximum Mobility Range & 10 m/round \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters for evaluating the proposed algorithm.  
The simulation runs for 2000 rounds, focusing on data communication efficiency and energy consumption. This setup aims to explore the dynamics of energy utilization and communication efficacy under varying base station locations to optimize sensor network performance and extend operational longevity.  
The main simulation parameters are selected as in [11] and listed in Table 1. To verify the energy efficiency of the proposed protocol, it was compared with the LEACH protocol, the K-means with LEACH protocol, and simulation with MATLAB for a network simulation and Python for graph visualization.