# A Hybrid Scheme for Disaster-Monitoring Applications in Wireless Sensor Networks
## 4 Scheme Description
### Set-Up Stage  
Clustering algorithms are very important for the network lifetime and delay performance of WSNs. The pLEACH algorithm is applied to cluster hierarchical sensor networks [46]. As previously mentioned, a collaborative disaster-monitoring system has a hierarchical architecture. The pLEACH algorithm is an adaptive clustering hierarchy algorithm with a high network lifetime and low communication delay. Based on centralized processing in the base station, the clustering algorithm first partitions the nodes into an optimal number of clusters and then selects the node with the highest energy in the cluster as the cluster head. In this study, we extend the pLEACH algorithm to heterogeneous sensor networks. In heterogeneous sensor networks, the clustering method also pursues the maximum network lifetime; that is, the death of the first node is averaged in a round. Data aggregation and relays occur in the cluster head (CH); therefore, the cluster head nodes consume more energy than the other nodes. The rotation of the cluster head may balance the energy dissipation of the sensor nodes. The decision metric used to select the cluster heads is  
Figure 2: Timeline of the HT-MAC scheme at the steady-state stage. important. We define \(T_{trutch}\) as the residual working time of the CH, as a cluster head, for the basis of cluster head selection:  
\[T_{trutch}=\frac{E_{r}}{P_{sc}+P_{ar}}, \tag{1}\]  
where \(E_{r}\) is the residual energy of a sensor node, \(P_{sc}\) is the mean power of sensing and calculation for this type of sensor node, and \(P_{ar}\) is the mean power of data aggregation and relay as a cluster head for a sensor node. \(T_{trutch}\) indicates the persistent working time if a node is selected as a cluster head. In this study, energy models similar to those proposed in [39] were used. The energy consumption of radio transmission can be calculated as follows:  
\[E_{Tx}(l,d)= \begin{cases}IE_{acc}+le_{fs}d^{2},&d<d_{0}\\ IE_{acc}+le_{mp}d^{4},&d\geq d_{0}\end{cases} , \tag{2}\]  
where \(E_{Tx}(l,d)\) is the energy of \(l\)-bit message transmission over distance \(d\), \(E_{dirc}\) is the energy consumption for digital coding, modulation, filtering, and spreading of the signal, \(\varepsilon_{fs}\) is the energy consumption of short distance transmission, and \(\varepsilon_{mp}\) is the energy consumption of long distance transmission. In addition, \(d_{0}\) is the threshold of the distance and can be obtained when \(d=d_{0}\), in Equation (2):  
\[d_{0}=\sqrt{\frac{\varepsilon_{fs}}{\varepsilon_{mp}}}. \tag{3}\]  
For receiving an \(l\) bit message, the radio expands  
\[E_{Rx}(l)=IE_{elc.} \tag{4}\]  
The proposed clustering algorithm is a centralized cluster head selection scheme. Only the base station is responsible for the cluster division of the entire network. Base stations generally have a continuous power supply, high storage and computing power, and global network information. Therefore, a complex algorithm can be used to obtain optimized clustering results. The proposed clustering algorithm comprises two phases. In the first phase, each sensor node sends its location and current energy to a base station using the CSMA/CA approach. According to this information, the base station obtains the optimal number of clusters [39]. Ordinary nodes are divided equally into sectors; thus, there are approximately equal numbers of ordinary nodes in each sector. Subsequently, all sensor nodes in a sector, including ordinary and superior nodes, form a cluster. The cluster head is selected from the ordinary nodes in a cluster. Therefore, the distance from any non-head node to the cluster head is less than the network radius, which reduces the overall communication energy consumption in the network. In the second phase of the proposed clustering algorithm, the cluster head is selected. When the network is initialized, each sensor node sends a report message to the base station regarding its current energy and location.