## 5 Evaluation Results: Influence of Each Layer to the Overall Performance
### APL Layer
If a packet really gets lost during a (re)transmission, the reaction time to the loss is constant, even after subsequent losses, contrary to the algorithms that apply a backoff. This assures a fast recovery from packet losses and helps to keep the delay low, even if the packets are lost consecutively. On the other hand, if the retransmission of the data packet is spurious and the network suffers from congestion, a quick retransmission may increase the congestion even further. This aggressive behavior comes at the cost of the lowest overall PDR and the highest amount of RTO expirations among the investigated RTO value calculation approaches (see Figure 19). By adding a backoff to the default algorithm, the ZigBee RTO algorithm with BEB achieves higher PDR at the cost of higher delays for medium and high traffic scales. When compared to the default ZigBee RTO algorithm, the CoAP RTO algorithm delivers a noticeably better performance in terms of PDR. Because of the large initial RTO value, spurious retransmissions are not likely. This positively affects the amount of RTO expirations (Figure 19). The drawback of such a large initial RTO value is the large amount of time that has to pass until a packet loss is detected. Independent of the amount of traffic, this causes the average delay and current consumption of the CoAP algorithm to be the largest, as seen in Figures 17 and 18. The performance of the CL algorithm heavily depends on the network condition during the route discovery and the RTT-multiplier \(K\). For \(K\) = 4, the CL algorithm performs on average slightly better than the default algorithm in terms of PDR for all traffics and in terms of delay with low and medium traffic. The energy efficiency of the CL algorithm on average is very similar to the one obtained by the default algorithm. However, it is important to point out that the values calculated by the CL algorithm varies strongly with the route hop count. Since the RTO value is a multiple of the RTT in this case, short routes with a low end-to-end delay will have a relatively short RTO value compared to long routes with a large delay. These differences in RTO values cause the behavior of the CL algorithm to be adapted to the number of hops of a path. Overall, this algorithm provides higher PDR than the ZigBee algorithm, lower delay (except for high traffic), a similar energy efficiency and a lower amount of RTO expirations. Figure 19: Relative amount of RTO expirations as seen from the application (APL) layer, when using different RTO value calculation algorithms, taking the default ZigBee RTO method as the reference. Experiments with higher \(K\) values led to higher overall PDR, but also larger delay. Smaller values led to the opposite effect, offering lower overall PDR and a shorter delay. Choosing \(K\) to be four provided a good tradeoff in the considered scenarios. The RFC 6298 algorithm performs slightly better than the default ZigBee algorithm at all traffic scales in terms of PDR, while the average delay is slightly smaller at low and medium traffic. At high traffic, the delay is larger for the RFC 6298 algorithm. In terms of energy efficiency, it performs slightly worse than the default algorithm in all traffic scenarios. In TCP, this algorithm is used to maintain an accurate estimation of the RTT during a transport layer connection. This normally involves the exchange of multiple packets between the endpoints of the transmission. Using this RTT information allows the sender to dynamically adapt the RTO value for subsequent transmissions to a specific destination. This means, however, that for end-to-end data transmissions with few packets, as are expected in a WHAN, the algorithm may not develop its full potential: the majority of events happen infrequently and only require a single data packet to be transmitted from the source to the destination node.