## 4 Performance Evaluation
### Network Lifetime Prolongation and Coverage Preservation  
In this section, we present the evaluation results for the performance of the CoCMA with respect to network lifetime prolongation and coverage preservation. The CoCMA is applied to the sink and used to control the activation or inactivation of sensor nodes to maintain higher coverage ratio of POIs with energy efficiency. In this scenario, we suppose that there are 64 POIs and 400 nodes distributed uniformly in a sensing field with size of 100 m \(\times\) 100 m. The initial energy for every node is the same, and all the nodes are assumed homogenous. Similarly, the nodes share the same sensing range of 17.675 meters and can communicate directly with the sink and other nodes in the sensing field. The corresponding parameters of this simulation scenario are summarized in Table 2. Additionally, the nodes are deployed to form a CWSN [26]. For the simulation scenario of uniform deployments, the redundant nodes can be efficiently found by the CoCMA and then be inactivated to conserve energy. Figure 8 (left) shows the initial deployment of nodes and POIs. Based on the proposed MA-based schedule for nodes, the redundant nodes are determined and inactivated. The remaining nodes are still activated and they are responsible to perform sensing tasks. Figure 8 (right) shows the coverage for POIs after applying the MA-based optimal schedule. In this simulation case, only 2.75% of nodes need to be activated to cover all POIs, which are all 1-coverage. Figure 9 shows the random deployment for a CWSN with POIs. The adopted parameters for the network are summarized in Table 2. In this simulation, there are 100 nodes and 100 POIs randomly deployed in a 50 m \(\times\) 50 m sensing field, as shown in the left of Figure 9. At this stage, the CoCMA is not applied yet. We note that there are many redundant sensor nodes in this sample network. After applying the CoCMA to the network, the new coverage for POIs is depicted in the right of Figure 9. It is clearly seen from this figure that a better energy-efficient coverage is achieved. The simulation data shows that 72% of the sensor nodes have been switched to a sleeping mode by the assistance of the CoCMA. In this case, only 28% of sensor nodes need to be active. This simulation demonstrates that the given CWSN using the CoCMA is able to monitor all 1-covered POIs and achieves a full coverage. \begin{table}
\begin{tabular}{l l} \hline a) & The sensing range \(r_{s}\) is 17.675 meters. \\  & \(\lambda\) is 1. Nodes with distance less than 17.675 meters are defined as neighbors. \\  & \(\eta=20\). \\  & \(E_{elec}=50\) nJ/bit, \(E_{amp}=100\) pJ/bit/m\({}^{2}\), \(E_{DA}=5\) nJ/bit/report, \(\beta=2\). \\  & \(E_{e}\) A sink is located at the coordinate (50, 200), which is far from the sensing field and power-rich. \\  & \(\mathrm{f}\)) The size of every data packet is 2,000 bits, i.e., \(H=2\),000. \\  & \(\mathrm{g}\)) Initial energy = 0.25 Joules. \\ \hline \end{tabular}
\end{table} 
Table 2: Parameters used in the CWSN-type sample network. In the next simulations, we will verify the feasibility of applying the proposed algorithm to a CWSN [26]. The sink node with sufficient power is able to arrange the optimal schedule for every node in the sensing field. When one node exhausts its energy, the wake-up scheme in the CoCMA can determine which neighboring nodes need to be awakened to recover the uncovered POIs. Therefore, the sensing coverage ratio and the number of active nodes are managed simultaneously. To compare the performance of the CoCMA with other four algorithms, simulations were conducted using the same sample network mentioned earlier under uniform deployments of nodes and POIs. The simulation results are compared to those of the Grid-Based Data Gathering Scheme (EGDG) [27], LEACH-Coverage-U [28], LEACH [26] and PEGASIS [29]. Figure 10 depicts the sensing coverage ratio versus the number of rounds.