## 7 Experimental Results
### Comparing between BEEM, Self-Concern Solution and Smart-BEEM  
Since it is normally assumed that only one communication interface exists in the traditional WSNs, choosing the nearest CH can maximally reduce the power consumption on the sensor nodes. Same as most existing work, one assumption in BEEM for the network is that  
_All the nodes are homogeneous and have similar communication and computation capabilities._  
This assumption can be seen in most studies for clustering. However, it will no longer be true in the high dynamic IoT systems. When the sensors are able to communicate through MIMO channels, we must be able to modify BEEM to adopt to this feature. In this section, we will illustrate the benefit for utilising this feature. Three approaches are analysed and compared:  
1. **Original BEEM:** Ignoring the MIMO feature, the sensors always use the communication interface with the highest bandwidth to guarantee the QoE for both _Video_ and _Data_ transmission. The nodes still choose the nearest CH to join. If no CHs are in the default cluster radius range, the nodes will transmit date back to the BS directly.
2. **Self-concerned BEEM:** In this approach, the nodes are aware of the multiple communication interfaces. However, each node will only choose its most preferred communication interface. If no CH in the range of this communication interface is available, it will halt the CH selection process and transmit data back to the BS directly using high power long distance communication (NAI\({}_{5}\)).
3. **Smart-BEEM**: BEEM algorithm is carried out firstly to elect CHs. Based on Smart-BEEM algorithm, each node selects a communication interface and CH with the highest QoE value. If no CHs are in range, same as above, the node will transmit data back to the BS directly though the default interface--NAI\({}_{5}\).  
As described before, Self-Concerned BEEM and Smart-BEEM are both based on BEEM. BEEM is focusing on CH election. Self-concerned BEEM and Smart-BEEM aim to facilitate IoT nodes to select communication interfaces and CHs according the current context. As we can see from Figure 10a, Self-Concerned BEEM can maintain the number of alive sensors better than the original BEEM. Furthermore, Smart-BEEM exceeds both original BEEM and Self-Concerned BEEM in terms of maintaining the number of alive sensors. Figure 10b has shown that Self-Concerned BEEM has maintained the coverage slightly better than the original one. Smart-BEEM has significantly increased the coverage at each round comparing with the other two solutions. When applying the original BEEM clustering algorithm in the network, the MIMO feature was ignored by the applications. In order to guarantee QoE, communication interfaces with high bandwidth were always prioritised. Since some of the sensors were only transmitting simple data information, energy consumption can be reduced through using low energy consumption interface if the sensors could be aware of the MIMO feature. Self-concerned BEEM can be aware of the requirements from the application and also the MIMO features. It can select suitable interface based on its own requirements. Therefore, its performance was better than the original BEEM. Further improved based on Self-BEEM, Smart-BEEM can also be aware of the context of the network. It can outperform Self-BEEM by selecting more suitable CHs for more energy efficient routing. The experimental results have proved our point of view--the ability of context awareness can further improve QoS and QoE When a sensor is aware of (1) the application requirements, (2) the MIMO feature and (3) network context, it can make the best decision for data transmission.