# A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks +
## 5 Simulation Results and Discussion
Figure 10d illustrates that when the node speed increases, the rate of _CH_ change goes high since the topology of network changes dramatically. Considering group mobility of network, the performance of RE\({}^{2}\)WCA is better than DWCA and EDWCA protocols. The rate of _CH_ changes in RE\({}^{2}\)WCA is nearly lower 7.5% than DWCA, 2.5% than EDWCA. In addition, our protocol can be used into a cluster structure routing protocols, in which higher tier nodes should have more residual energy. Our approach can also be effective for sensor applications requiring efficient data aggregation and prolonged network lifetime. In the simulations, most of parameters are similar to those in [2; 19; 20; 34]. Additionally, the mobility speed of nodes is 10m/s which is also similar with Ref [14; 42; 43]. The parameters are listed in Table 2. The energy consumption computing of sensor nodes is on the basis of Equations (1)-(3). Except for the above parameters, without loss of generality, the application parameters are as followed: data packet size of 100 bytes, broadcast packet size of 25 bytes and packet header size of 25 bytes [3; 10; 34]. Additionally, we assume a = 0.7, b = 0.3 as the weighted average index. The reasonability has been discussed before. Firstly, all network has to solve the problem of throughput. For the purpose of increasing the throughput of the network, clustering method for nodes is adopted. Figure 9: Features of elected CHs. (**a**) Percentage of CHs. (**b**) Average residual energy per _CH_. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Parameters** & **Significance** & **Value** \\ \hline \(N\) & Total numbers of nodes & 50 \\ \(m\times n\) & Network size & 100 m \(\times\) 100 m \\ _MaxSpeed_ & Maximum movement speed & 10 m/s \\ _time\_fn1_ & Fault node detection period & 20 min \\ _time\_fn2_ & _CH_ fault detection period & 30 min \\ _Round_ & data transmission frequency & 5 TDM frames \\ \(T\) & Simulating time & 800 min \\ \(E_{initial}\) & Initial energy & 2 J \\ \(E_{\text{\emph{e}}lec}\) & Activating energy & 50 nJ/bit \\ \(E_{\text{\emph{f}}nison}\) & Energy consumption of data fusion & 5 nJ/bit/signal \\ \(\varepsilon_{amp}\) & Amplification coefficient (\(d>d_{0}\)) & 0.0013 pJ/bit/m\({}^{4}\) \\ \(\varepsilon_{f\text{\emph{s}}}\) & Amplification coefficient (\(d<d_{0}\)) & 10 pJ/bit/m\({}^{2}\) \\ \(d_{0}\) & Threshold distance (\(d_{0}\)) & 75 m \\ \(D_{thr}\) & Cluster radius & 25 m \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation Parameters. Figure 10: Features of clusters. (**a**) Standard deviation of the number of nodes/cluster. (**b**) Percentage of non-single clusters. (**c**) Ratio of maximum number of nodes in RE\({}^{2}\)WCA to other two types protocol. (**d**) Rate of _CH_ changes with node speed varying. In Figure 11, the first node of the DWCA algorithm failed at 196 rounds and the first node of the EMDWCA algorithm failed at 331 rounds, while the first node of the RE\({}^{2}\)WCA algorithm failed at 398 rounds; the nodes that survive with the RE\({}^{2}\)WCA algorithm is 103% higher than that of the DWCA algorithm and 20% higher than that of the EMDWCA algorithm. We also know that, when using the DWCA algorithm, all nodes are dead after 721 rounds of cluster head election. By applying the EMDWCA algorithm the life cycle of the node is 1270 rounds, however, by using RE\({}^{2}\)WCA algorithm the surviving nodes remain to exist after 1410 rounds. This is because the algorithm proposed in this paper not only considers the residual energy and the mobility of the node but also takes the maximal capability of cluster head handling into account, which makes the nodes' energy consumption more homogeneous and protects the cluster heads from excessive consumption. So, the RE\({}^{2}\)WCA algorithm improves the stability of the network topology and the survivability of the overall network. Figure 12 demonstrates the average network throughput varies with the distance of nodes.