# Parent and PHY Selection in Slot Bonding IEEE 802.15.4e TSCH Networks
## 5 Evaluation
### Experiment Methodology & Setup
#### 5.1.2 Testbed Experiments  
The proposed heuristic was also validated on the _innec Wireless OfficeLab_, using the TSCH slot bonding proof-of-concept discussed in Section 4[26]. The testbed was located in an office environment spanning different floors of 805 m\({}^{2}\) separated by reinforced concrete, with a total of 150 sensor nodes of which a subset of 13 nodes was used as illustrated in Figure 5. The deployed sensor nodes were the Zolertia RE-motes[27]. Figure 6 shows several of the deployed sensor nodes in the office environment. The testbed evaluation was a 3-step process as illustrated in Figure 7. First, using the slot bonding implementation, the link reliability between all nodes was monitored, in both directions, for the 50 kbps and 1000 kbps PHYs (as listed in Section 4.2). Every link was monitored for 300 s, transmitting a packet of 127 bytes every second, and its reliability was defined as the average \(\frac{num\,ACK_{8}}{num\,TX}\) of five consecutive observations, each over a time span of 60 s. The monitored link reliability values are publicly available ([[https://github.com/imec-idlab/officelab-reliabilities](https://github.com/imec-idlab/officelab-reliabilities)]([https://github.com/imec-idlab/officelab-reliabilities](https://github.com/imec-idlab/officelab-reliabilities)), accessed on 9 May 2021). Links between nodes that did not connect or became disassociated during the experiment were assigned a reliability value of 0. Two different scenarios were considered, each with  
Figure 5: The two floors of the hardware testbed with the 13 used nodes illustrated at their locations. Two scenarios of 12 nodes were considered: scenario 1 includes the 11 grey nodes and the blue node while scenario 2 includes the 11 grey nodes and the green node. Figure 6: A subset of _innec Wireless OfficeLab_ sensor nodes, deployed on the ceiling in an office environment spanning different floors of 805 m\({}^{2}\), separated by reinforced concrete. 12 nodes as illustrated in Figure 5: scenario 1 included the 11 grey nodes and the blue node while scenario 2 included the 11 grey nodes and the green node. It turned out that, in normal conditions, the 1000 kbps PHY was able to connect (almost) all nodes with a very good reliability. Therefore, to better emulate an industrial environment in which the reliability of different network links can heavily vary and/or some nodes can not connect with certain PHYs, different transmission powers were used for the 2 PHYs and a part of the 1000 kbps PHY links was disabled in both scenarios. For the 50 kbps PHY, the transmission power was set to 14 dBm, while for the 1000 kbps PHY it was set to 0 dBm. Additionally, uniformly at random, 70% of the 1000 kbps PHYs links of each node (i.e., assigning links a reliability value of 0) were disabled. The goal of the monitoring step was to determine the link reliability values of all nodes to each other for each PHY, as these would be used by the heuristic to make the parent and PHY selections. While this monitoring step simplified our evaluation of the heuristic, in an integrated solution this could be replaced with run-time statistics as explained in Section 3.6. As such, afterwards, these reliability values were fed, together with the slotframe information and the selected set of nodes (including a randomly selected root node), to the GA scheduler. In the case of the heuristic, the GA only decided the slot allocations as the heuristic determined the parent and PHY selection for each node. Finally, the resulting network topologies with selected parents and PHYs and the TSCH schedules were configured on all selected nodes in the hardware testbed and the results were monitored for 300 ms.  
Figure 7: Flow diagram illustrating the testbed evaluation process. The testbed link monitoring information was used as input for the heuristic (with the GA for slot allocations) or the GA, and the outcomes of those schedulers were loaded on the sensor nodes in the testbed.