## 8 Simulation Assessment
### Simulation Environment  
For this simulation assessment, it was considered a communication environment with a size of 200 m \(\times\) 200 m, composed of 201 sensor nodes (one PAN coordinator, plus 200 sensing nodes). The PAN coordinator was located in position 5 m \(\times\) 5 m of the environment, while 200 sensing nodes were randomly deployed. The PAN coordinator node was deployed in the corner of the environment, in order to build deep cluster-tree networks. Figure 11(a) illustrates an example of the simulation environment used in this assessment. Regarding the monitoring traffic, sensing nodes generate periodic messages and send them to sink node (PAN coordinator). For the sake of simplification, we defined that each sensing node supports one message stream and that PAN coordinator does not generate any traffic itself. Each sensing node generates 1000 data messages, sending them to the PAN coordinator according to the rules defined by IEEE 802.15.4/ZigBee data communication. Thus, data messages are forwarded along the cluster-tree network according to the tree routing protocol. Importantly, cluster-heads do not perform any data aggregation or fusion mechanism, which implies that all monitoring traffic is forwarded towards the sink node. In order to generate different message loads for the cluster-heads, we defined two different data rates for the set of message streams: a higher data rate (0.05 pkts/s--periodicity of 20 s), and a lower data rate (0.01 pkts/s--periodicity of 100 s). The cluster-tree formation process is based on the IEEE 802.15.4 standard/ZigBee specifications. The PAN coordinator (defined as depth 0 of the cluster-tree network) is responsible to trigger the formation procedure, by building its own cluster and acting as cluster-head. We defined the maximum number of child nodes per cluster to be 6 (six). For this simulation assessment, we have defined two cluster-tree formation procedures, in order to create two different simulation scenarios: an unconditioned cluster-tree (hereafter called _unconditioned Scenario_) and a conditioned cluster-tree (hereafter called _conditioned Scenario_). In the first scenario (unconditioned formation), each CH (including the PAN coordinator) can select a maximum number of 2 (two) candidate child nodes to be cluster-heads. The selection of CH candidates is randomly performed and the cluster-tree network can grow in any direction. Each CH candidate can build its own cluster, following the same rules. The data rates are randomly distributed along the sensing nodes in the network environment. Figure 12 shows an example of the unconditioned Scenario._ Figure 12a illustrates the data rates randomly distributed along the environment, while Figure 12b illustrates an example of the physical topology for the _unconditioned Scenario_. In the second scenario (conditioned formation), we have equally divided the environment in two different load zones: high load zone, and low load zone. Nodes located in the high load zone are configured with data rate of 0.05 pkts/s (higher data rate), whereas nodes located in the low load zone are configured with data rate of 0.01 pkts/s (lower data rate). Considering these two different load zones, the cluster-tree formation process is started by the PAN coordinator, which selects one CH candidate in the high load zone and another candidate located in the low load zone. Following, each cluster-head can select a maximum number of 3 (three) CH candidates, that must also be located in the same load zone of their parent CHs. Therefore, we have a conditioned cluster-tree network, where one branch is built along the high load zone and the another branch is built along the low load zone. Figure 13 shows this _conditioned Scenario_. Figure 13a illustrates the two defined load zones (high and low load zones), while Figure 13b illustrates an example of a physical topology for the _conditioned Scenario_. Table 3 summarises the main features of the _unconditioned_ and _conditioned Scenarios_.