## 5 Performance Evaluation and Analysis
This is because nodes in CS-DDSG receive packets only the first time and broadcast their packets with the probability \(\mathbf{p_{2}}\), after which then they do not receive any data. However, for CNCDS, CStorage and ICStorage, nodes continue to receive packets as long as the reception condition is satisfied. Cstorage and ICStorage in particular focus on reducing the number of transmissions. Moreover, compared with CNCDS, CStorage and ICStorage, CS-DDSG scheme reduces \(\mathbf{N_{Ttot}}\) by up to 23.9%, 42.5% and 67.8%, respectively, and reduces \(\mathbf{N_{Rtot}}\) by up to 73.8%, 80.2% and 89.9%, respectively. Figure 10: The total number of transmissions, receptions and fusions in Stages 2 and 3. Figure 9: Performance of the different algorithms in unreliable links: (**a**) DDS-based algorithms; and (**b**) comparison between DDS-based algorithms and cluster-based algorithm. Furthermore, we investigate the fusion proportion of the total number of receptions. As presented in Figure 11, only 41% of the receiving nodes in CNCDS merge the received packets; the authors consider that only 41% of nodes lose energy. In fact, 59% of the receiving nodes also consume energy because they would receive the broadcast packet first and then determine whether the condition of CNCDS are satisfied; the received packets will be merged only if they satisfy the condition. Thus, energy is consumed even when the received packets are not fused. However, the number of receptions in [21] is the same as the number of fusions, which is less counted. Similarly, 46% and 48% of the receiving reception nodes in CStorage and ICStorage merge the packets, respectively. In CS-DDSG, all received nodes are fused and no redundancy occurs because the nodes receive packets only once. Thus, the energy consumption of CS-DDSG receiving nodes is much smaller than that of the other algorithms. In conclusion, CS-DDSG effectively reduces both the number of transmissions and receptions. Figure 12 presents the number of fusions and receiving nodes during each forwarding round when \(\mathbf{p_{1}=0.15}\). The forwarding process of CS-DDSG repeats five times, until no node remains to accept the broadcast packets, while CNCDS, CStorage and ICStorage repeat six, nine and twelve times, respectively. The network employing CS-DDSG has the fastest convergence and characteristics of efficiency due to the strictest reception conditions. Moreover, most of the data fusion occurs during Stage 2, and subsequently the number of fusions rapidly decreases in Stage 3 except in ICStorage. In Figure 13, we investigate the recovery performance of the algorithms when \(\mathbf{p_{1}=0.3}\) and the number of measurements \(\mathbf{M}\), which is queried by the mobile sink, ranges from 15 to 150. It can be observed that, with an increase in \(\mathbf{M}\), the recovery accuracy of ICStorage, CStorage, CNCDS and CS-DDSG are improved and equivalent, while the performance of CS-DDSG becomes slightly better when \(\mathbf{M\geq 100}\). This improvement occurs because the more information that is gathered, the better is the reconstruction accuracy. According to Equation (12), the sink constructs measurement matrix \(\mathbf{\Phi}\) based on the packets fused by the forwarding nodes. The forwarding nodes of CS-DDSG receive only one packet, and the \(\mathbf{\Phi}\) is sparser than that in the others algorithms. Consequently, less information is gathered and fewer nodes contribute to data recovery for CS-DDSG. However, with an increase in \(\mathbf{M}\), more information is gathered and the gaps separating the four algorithms decrease. When \(\mathbf{M>100}\)  
Figure 11: The fusion proportion of the total number of receptions. CS-DDSG outperforms the four DDS-based algorithms due to the strong spatial correlation of the measurement vector. Moreover, the reconstruction accuracy of DCCS is the best when \(\mathbf{M}\) is large enough and there is no packet loss. All nodes in DCCS participate in gathering data and DCCS adopts dense measurement matrix in clusters.