# Improving Route Selections in ZigBee Wireless Sensor Networks
## 7 Performance Evaluation
### Symmetric Topologies
#### 7.1.3 Scenario S3: Two-Hop Scenario
Figure 8c shows the average of \(r_{3,6,1,0}+r_{3,7,2,0}\) for 30 simulation runs at each traffic level for the LS-based, the LQI-based, and the U-RR procedures. Figure 7: Topology with one-hop and two-hop routes. It is possible to see in Figure 8c that the LS-based procedure resulted in better route decisions than both the U-RR and the LQI-based procedures when the average number of packets/s generated by nodes was between 1 and 5 packets/s. To understand this, recall that the U-RR procedure selects the next hop node with the least number of packets transmitted when two RREQs arrive with the same cumulative cost. When the traffic load is low, packet losses due to the hidden node problem are low, and although \(c_{3,6,1,0}<c_{3,6,2,0}\), the sum of 3-bit quantized link costs may result in the same value, and the U-RR procedure would result in node 6 selecting node 2 as the next hop towards node 0 more often to better estimate its actual cost. However, when the average number of packets/s generated by nodes was between 5 and 12.5 packets/s, the U-RR procedure resulted in better route selections than both the LQI-based and the LS-based procedures. In some cases, the U-RR procedure chose one of the preferred routes 3,6,1,0 and 3,7,2,0 more than 90% of the time, while the LQI-based and LS-based procedures selected the preferred routes around 55% and 75% of the time respectively. When the average number of packets/s generated by nodes was very large (above 12.5 packets/s in this case), both the LS-based and the U-RR procedure reached similar performances. To understand this, note that higher traffic loads increase the frequency of hidden node problems. If the traffic load is high enough, the difference in cost of candidate routes becomes wide enough that, even with the higher variation of the LS-based procedure, the noisy cost estimate of routes 3,6,1,0 or 3,7,2,0 is still above the noisy cost estimate of routes 3,6,2,0 or 3,7,1,0. Figure 8: The median and the 15 th to 85 th percentiles of (**a**): the cumulative route cost of routes 3,7,\(\times\),0 (\(c_{3,7,\times 0}\)), (**b**): the standard deviation of the estimated costs measured at node 3 for the routes 3,7,\(\times\),0 (\(c_{3,7,\times 0}\)), (**c**): the ratio of times that packets were relayed by the best routes 3,6,1,0 and 3,7,2,0 (\(r_{3,6,1,0}+r_{3,7,2,0}\)), and (**d**): the delivery rate of messages originated at nodes 3, 8, and 9 in the symmetric scenario S3. Lastly, since \(c_{3,6,1,0}=c_{3,7,2,0}<c_{3,6,2,0}=c_{3,7,1,0}\), we also evaluated the impact of choosing the suboptimal routes 3,6,2,0 or 3,7,1,0 in the packet delivery rate of each procedure. Since the routes were not being chosen directly by node 3, we computed the rate of successfully delivering messages. Also, because the procedures also select between route 8,6,1,0, route 8,6,2,0, route 9,7,1,0, and route 9,7,2,0, we computed the rate of successfully delivering packets from nodes 3, 8, and 9 for each procedure. As illustrated in Figure 8d, it is possible to note that the U-RR procedure performed slightly better than the LQI-based procedure when the traffic load was large; however, the difference with respect to the LS-based procedure was small, suggesting that the amount of asymmetry was not large enough to cause an impact in the network delivery performance.