# Improving Route Selections in ZigBee Wireless Sensor Networks
## 7 Performance Evaluation
### Asymmetric Topologies
#### 7.2.2 Scenario A2: WiFi Interference  
Consider the topology shown in Figure 10, where ZigBee nodes 0, 1, 2, and 3 operate in a communication channel that overlaps with the channel used by a WiFi IEEE 802.11n network. Consider that the ZigBee nodes are in the same locations as in the Scenario A1 of Section 7.1.2 and the WiFi network again consists of one access point and two stations, but now at locations (60,\(-\)30), (60,\(-\)20), and (60,\(-\)40) respectively. Assume that node 3 sends application data at an average rate of 20 packets/s to node 0. At \(t=100\) s, the WiFi access point starts two data streams of constant-bit-rate traffic of \(R_{WiFi}\) bits/s, one to each WiFi station; and these streams last until the end of the simulation at \(t=400\) s. Details of these streams are as described in Section 4. As in Scenario S2, the WiFi devices are far from node 3 and may transmit while node 3 is transmitting; however, because the WiFi devices are closer to node 1, the interference level increases at node 1 and decreases at node 2, resulting in \(c_{3,1,0}>c_{3,2,0}\). In this case, it is desirable that node 3 chooses the route 3,2,0 as much as possible since node 2 is less subject to the WiFi interference. To analyze the performance of the U-RR procedure in selecting the best route 3,2,0, we varied the traffic level generated by the WiFi access point, and at each traffic level, we repeated the simulation 30 times, each time with a different random seed. Figure 11a through Figure 11f respectively, show the median and the 15 th to 85 th percentiles of the cumulative route costs 3,1,0 and 3,2,0 (\(\overline{c}_{3,1,0}\) and \(\overline{c}_{3,2,0}\)), their standard deviations (\(\sigma_{3,1,0}\) and \(\sigma_{3,2,0}\)), the ratio of times that route 3,2,0 was chosen (\(r_{3,2,0}\)), and number of times that node 3 had to retransmit per 1000 messages generated for 30 simulation runs as WiFi traffic load \(R_{WiFi}\) varied for the LS-based, the LQI-based, and the U-RR procedures. Figure 10: Topology where ZigBee devices share same spectrum as WiFi devices. Figure 11a,b show that, as the \(R_{WiFi}\) increased above 450 kbps, both the LS-based and the U-RR procedures started to detect the higher cost of the route 3,1,0 with respect to route 3,2,0, while the LQI-based procedure still considered both routes having the same cost. It is interesting to observe that the \(\overline{c}_{3,1,0}-\overline{c}_{3,2,0}\approx 0.5\) in the LS-based procedure, within the standard deviation of the estimates, while \(\overline{c}_{3,1,0}-\overline{c}_{3,2,0}\approx 2\) in the U-RR procedure, showing that the U-RR procedure was able to better recognize route 3,2,0 as the best route. It is also interesting to observe that the standard deviations \(\sigma_{3,1,0}\) and \(\sigma_{3,2,0}\) are not significantly affected by the U-RR procedure. Figure 11: The median and the 15 th to 85 th percentiles of **(a)**: the cumulative route costs of the route 3,1,0 (\(\overline{c}_{3,1,0}\)), **(b)**: the cumulative route costs of the route 3,2,0 (\(\overline{c}_{3,2,0}\)), **(c)**: the standard deviation of the estimated costs measured at node 3 for the route 3,1,0 (\(\sigma_{3,1,0}\)), **(d)**: the standard deviation of the estimated costs measured at node 3 for the route 3,2,0 (\(\sigma_{3,2,0}\)), **(e)**: the ratio of times that route 3,2,0 was chosen (\(r_{3,2,0}\)), and **(f)**: the number of times that node 3 had to retransmit per 1000 messages generated in the scenario A2. of the LS-based procedure reduced for higher WiFi loads. This behavior can be explained by observing the cumulative route costs \(\overline{c}_{3,1,0}\) and \(\overline{c}_{3,2,0}\): when the WiFi load increased, there was a point in which the cumulative route costs increased above 8. Remembering that each individual path cost is quantized between 0 and 7, this suggests that \(c_{1,0}\) and \(c_{2,0}\) started to saturate at 7, reducing the variations in cost.