## 3 Proposed Fires Monitoring and Detection Framework
### The Proposed Sensor Deployment Scheme
Overall, Figures 2-4 indicate that the proposed deployment scheme has less contribution to the performance of energy efficiency and fire reaction delay compared to the regular deployment scheme due to its inherent natures. However, in the forest environment, it is impossible to deploy all sensor nodes with a regular grid pattern in large scale. Hence, to improve the performance of energy efficiency and fire reaction delay, we require some extra facilitation. #### 4.2.2 Performance Evaluation on the Proposed Clustered Hierarchy Network Architecture

In this subsection, we compared our proposed E-LEACH with the flat topology applied in forest fire monitoring and detection application in terms of total data throughput and energy consumption. Figure 5 depicts the relationship between the number of sensors in a cluster and the total data throughput carried in the network which adopts our proposed scheme. Initially, the number of nodes in a cluster is small, and the total data throughput in the network is relatively higher. This is because at this moment, each sensor node should sense the environmental condition more frequently and generate more sensory data and control messages to guarantee the accuracy of the system. As the number of nodes in a cluster increases, the throughput of the network is reduced. Another important finding in this simulation is



Figure 6 gives the data throughput of the network varying with simulation time when flat topology is adopted. The average throughput of the network in this case is 0.013 Mbit/s. As compared to Figure 5, we can see that the proposed clustered hierarchy topology has less average data throughput. Furthermore, less data throughput involved in the network will reduce energy consumption. Figure 7 presents the comparison of the total consumed energy by the networks that adopt the proposed clustered hierarchy topology and flat topology, respectively. From the results we can observe

Figure 5: Relationship between the number of sensors in a cluster and the total data throughput in network. Figure 6: Data throughput of the network which adopts flat topology. that the proposed topology consumes less energy compared to flat topology. There are two reasons contributing to this superior performance. First, the proposed topology is clustered and hierarchical, which involves less data throughput in the network and further reduced the energy consumption. Second, less energy consumption is due to the unnecessary sensor nodes in a certain cluster, and should always sense the environmental condition. The cluster head schedules each node to be active. Meanwhile, we can find that initially the proposed topology consumes more energy than the flat topology. This is because at the moment, the proposed topology is in the process of clustering, which will consume more energy. #### 4.2.3 Performance Evaluation on the Proposed Intra-Cluster and Inter-Cluster Protocols

As discussed earlier, our proposed protocols are environmentally aware. That is, the protocol actions include both intra- and inter-clusters and how frequently the data are sensed is determined by multiple factors such as the location of the forest, the climate, and the season etc. In this subsection, we are going to evaluate the performance of the proposed environmentally aware protocol in terms of energy consumption and fire reaction delay. For evaluation purpose, we compare the proposed scheme against a base scheme which does not consider the current environment conditions while making decisions and actions. Figure 8 gives the energy consumption of the proposed scheme and base scheme. As the figure shows, the energy consumed in the base scheme is constant throughout the simulation time. Here, in fact, we can define the simulation time as months of year. This is because our proposed protocol takes into consideration the influence from the seasons. On the other hand, the energy consumption of the proposed scheme depends on the season.