## 4 Performance Evaluation
### Simulation Result
In addition, the data collected by ERG-NCS are much less repetitive and redundant than that without considering the coverage algorithm, which means that the data collected by ERG-NCS are the most effective. It is evident from Figure 16 that ERG's link repair effect makes it much more reliable than RTG and AMSG, the nodes can determine the state of the communication link, and as long as a valid node is selected as the next hop, then the data can definitely be transferred back to the sink successfully. After scheduling the network nodes, having fewer monitoring  
Figure 14: Coverage rate with different number of rounds. Figure 15: Throughput with different number of rounds..  
nodes also results in more alternative paths for data transmission, allowing the network to maintain a high PDR for an extended period of time. Additionally, an excellent node collaboration model, nodes' scheduling and link repair capabilities enable ERG-NCS to outperform others significantly in terms of PDR. Figure 17 shows how the network overhead varies with the number of nodes. The ERG-NCS algorithm suffers from packet loss only if the link cannot be repaired, and in most cases, especially when the death number of nodes in the inner area is low, the data are usually transmitted back to the sink successfully. Therefore, the network overhead of ERG-NCS is the lowest, and it suffers from the smallest number of packet loss, while the sink receives the most data. For RTG and AMSG and their derived algorithms, the communication of the network cannot be guaranteed exactly because geographic routing possesses a certain degree of blindness, so their network overhead will be higher. Next, we explore how the average end-to-end delay of ERG varies with the communication radius for the three cases of using the no scheduling algorithm using the disk-based greedy scheduling algorithm and using the node collaborative scheduling algorithm, the network parameters are the same as the above. Since geographic routing has low latency, this advantage continues to be magnified by combining routing with coverage control techniques. We can apparently understand from the illustration of Figure 18, the lesser the number of nodes working, the lesser the number of paths generated which results in lesser congestion in the network and lower latency in the network. NCS and DGS reduce the number of nodes working to a great extent and hence the latency is much lower than when coverage scheduling algorithms are not used. As the communication radius increases, the number of  
Figure 16: Network PDR with different number of rounds. Figure 17: Network overhead with different number of nodes. hops for data transmission will be less and hence the average delay of the network is lower. NCS has the least number of working nodes which leads to the lowest delay. Finally, we analyze the complexity of the proposed algorithms. As far as the complexity analysis of the algorithms for each sensor node is concerned, they all derive their computation from the information interactions with the neighboring nodes; the location and remaining energy of each neighboring node need to be obtained in the improved geographic routing protocol. A few nodes need to obtain the new location of the sink in the tree-based routing protocol; the same is conducted for obtaining the valid state and remaining energy of the neighboring nodes in the link detection and repair protocol. Each protocol relies on these interactions to take the next action, and only one loop needs to be executed. Therefore, the program running inside each sensor node has an algorithmic complexity of \(O(n)\), the size of \(n\) depends on the number of neighboring nodes. In addition, after the NCS algorithm, the amount of data received by the sink within each round is greatly reduced, which means that the sink does not have to receive and process a large amount of data within a short period of time, which greatly reduces the burden of the sink and contributes to the stability of the whole network.