## 5 Experimental Results
the transmission power increases). Since larger transmission power allows  
Figure 14: The regression analysis between the network response and the corresponding targets: 1-hop regression analysis (left) and 2-hop regression analysis (right). Figure 15: The relationship between the number of sensing rounds \(N_{RG}\) in a cluster and transmission range \(R\) with varying the number of sensors. larger radio coverage, a cluster has more cluster members, which increases the coverage overlap and results in a larger \(N_{RG}\) in a cluster. Thus, a large \(R\) may result in heavy sensing redundancy due to a large number of neighboring sensors. On the other hand, a small \(R\) may produce many isolated sensors in a network. Therefore, a sensible transmission range is essential to explore the performance of the scheduling approach. In [35], the authors suggest that \(R\approx l\sqrt{\frac{\log l}{N_{s}}}\) may be a good choice for the initial range assignment for sensors in the _2_-dimensional space, where \(N_{s}\) is the number of sensors. As a result, the clusterhead may adaptively manage the scheduling operation based on the data gathering strategy and an appropriate transmission range \(R\) in order to avoid severe communication interference. Figure 16: The comparison of the average number of round groups \(N_{RG}\) applying the proposed scheduling schemes and those using the analytical models. Figure 17: The number of active nodes in a round \(M_{RG}\) with varying the transmission range \(R\). the sensing compensation from nearby clusters results in a higher percentage of sensing coverage in a network. Similarly, given the same network topology, the operation of the DASA scheme achieves \(55\%\) average sensing coverage in a cluster and \(80\%\) average sensing coverage in a random network. Since the CASA scheme executes the scheduling management in a centralized way, it may have better spatial arrangement of sensors in each round compared with the DASA scheme. Figure 7:0 The distribution of the number of sensing rounds \(N_{RG}\) applying the proposed scheduling schemes and those using the analytical models with \(N_{s}=200\). Figure 7:1 The coverage percentage of the whole network and each cluster (the top-right quadrant); the accuracy of the neural network architecture (the bottom-left quadrant) and the accuracy of the Probabilistic Model (PM) in a random network (the bottom-right quadrant). The sixth set of experiments studies the network connectivity when using the proposed scheduling approaches. Given a random network with \(N_{s}=100\) and the period of the observation phase \(5T_{cycle}\), Figures 21 and 22 show the maintenance of network connectivity in round 1 and round 2. The circle ('o') represents the sleep node and a connection between a pair of distributed gateways ('\(\Box\)') is indicated by a dashed line. Observe that in order to conserve energy, the active nodes (the sensing node '\(\bullet\)' and the relay node '\(\blacktriangle\)') are good candidates for being gateways in each round. As demonstrated in Figures 21 and 22, although the network may not be fully connected in each round, the operations of the proposed schemes maintain sufficient network connectivity and provide a way for inter-cluster communication and data dissemination. By following the analysis as detailed in Section 4.4, the seventh set of experiments illustrates the mean memory usage in the cluster members and the clusterhead, respectively. Assume each node has a 36-byte data packet to transmit. Figure 23 (right) depicts the mean memory utilization for gathering the information in a clusterhead. Figure 23 (left) shows the total mean memory usage for running the proposed scheduling algorithms in the sensors in a cluster. As shown in Figure 23 (left), compared with the CASA, the cluster members consume more memory as establishing the sensing schedule with the DASA scheme. The main reason can be contributed to the tracking operation of round ID, which is used to create the order of sensing round.