## 5 Evaluation Results: Influence of Each Layer to the Overall Performance
### NWK Layer
Finally, note that the HC metric is not link quality-aware and, thus, may select both high and low quality links, but it guarantees the shortest route. \begin{table}
\begin{tabular}{|c|c|c|c|} \hline
**Metric** & **Low Traffic** & **Medium Traffic** & **High Traffic** \\ \hline BeeStack & 1.32 & 1.44 & 1.63 \\ HC & 1.30 & 1.45 & 1.64 \\ PLF & 1.22 & 1.38 & 1.59 \\ Path-DR & 1.28 & 1.47 & 1.67 \\ \hline \end{tabular}
\end{table} 
Table 4: Average number of tries that are performed by the MAC layer to transmit one unicast data frame for different metrics and traffic scenarios. Figure 14: Example topology, where the Path-DR metric only finds one best route between the source (S) and destination (D) (S-1-2-D), while the ZigBee path cost metrics (HC, BeeStack and PLF) find three routes of equal cost (S-1-2-D, S-3-2-D, S-3-4-D). The numbers on the links represent the LQI values of the links. Note that all ZigBee path cost metrics will assign the same cost to all of the links shown in this example (see Figure 2). Another important issue observed throughout experiments in the testbed environment is the negative effect of asymmetric links on network performance. Similar observations have been made in the literature [46]. Normally, the forward and backward links of a route between two nodes are of similar qualities in terms of LDR or LQI. However, it has been observed in the testbed environment that approximately 6% of all links between nodes are strongly asymmetric. These links are normally of very high quality in one direction and have a very bad or no connection at all in the other direction. For metrics that take into account the link qualities of the forward route towards the destination, asymmetric links can result in unsuccessful route discoveries, as RREPs may not be able to return to the source node. Figure 15 illustrates this situation. In this scenario, a route discovery would not provide a valid route, even though there exists at least one. The path cost for a route that includes the asymmetric link would be better for all metrics than the path costs for the alternative routes that do not include asymmetric links. The issue of asymmetric links affects especially link quality-aware metrics. This leads to higher channel usage (all retries are spent to forward RREPs that never reach their destination nodes) and also to higher buffer occupation inside the nodes (the buffers are occupied longer, while retries are spent). While this phenomenon affects all of the analyzed link quality-aware metrics, the larger diversity of possible routes that are found by the BeeStack and PLF metrics augments the probability of finding a usable route with these two metrics. The Path-DR metric, however, has a lower probability of finding alternative routes, since the route diversity is much smaller, as illustrated in Figure 14. This is another reason for the Path-DR metric to perform badly for medium and high traffic scales. Because of these observations, we recommend using an LQI to link cost mapping for the ZigBee path cost metric of medium granularity, which allows one both to discard low quality links and to assure sufficient path diversity, like in the PLF metric. There are several ways to address the problem of asymmetric links. One solution is to use asymmetric routing, where the forward and backward paths are not the same. This requires two separate route discoveries. The ZigBee Pro specification includes this feature as an optional mechanism. Outside the ZigBee specification, modifications of the default AODV, like R-AODV [47], implement asymmetric routing. Figure 15: A network topology, where an asymmetric, unidirectional link of high quality (dashed line) is likely to be chosen by the routing metrics, even though its asymmetry impedes RREPs sent by the destination (D) from being returned to the source node (S). The numbers represent the LDRs of the links.