## 6 Evaluation
### Experimental Results  
Using the testbed that we described previously, we compared the performance of two versions of ACTOR with the baseline, RPL, and the benchmark, TPP. Figure 9 shows the advantage of using ACTOR in terms of PDR, transmission power, and routing overhead as the traffic increases. Figure 8: Simulation results considering seven different scenarios showing: (**a**) End-to-end delay, (**b**) Packet Delivery Ratio, and (**c**) the current used for radio transmission. Figure 9a plots the aggregate packet delivery ratio of ACTOR, ACTOR-D, TPP, and standard RPL with different data intervals. The results suggest that the two versions of ACTOR provide better throughput (PDR) than TPP and RPL. When a smaller volume of traffic is applied to the network (5-s interval), ACTOR beats both RPL and TPP by almost 40 percent. In other words, ACTOR reduces the packet loss rate by four times compared to the standard. The advantages of using ACTOR in this scenario are better shown in the experiments than in the simulations. This stems from the fact that, in a realistic environment, none of the links are ideal. As we saw in Section 4, links behave randomly in the transitional region. In this situation, benchmarks cannot find a transmission power that transmits a number of consecutive packets successfully and select the maximum transmission power. UCB is able to find the best transmission power in those cases, but the benchmarks fails to adapt their simplistic transmission power control. The other reason is the local repair mechanism in the RPL protocol. Once nodes detect an abrupt change in the measured routing metric (ETX), they initiate the local repair mechanism of RPL, which consists of disconnecting from the parent and sending a DODAG Informational Solicitation (DIS) asking for a new parent. This can be seen in Figure 9c, which shows that the local repair mechanism causes more control packets (both DIO and DAO) for RPL and TPP compared to ACTOR. ACTOR-D slightly outperforms ACTOR in the 40-node experiment, thanks to the discounting mechanism. Nodes that keep changing their transmission power impair the wireless links belonging to other nodes. Hence, when nodes are not moving or when there is a dynamic source of interference, this may be the source of dynamism in the quality of the links, and ACTOR-D is tailored to handle this. Figure 9b that ACTOR and ACTOR-D successfully reduce the transmission power while providing better connectivity. For RPL, the transmission power is always at 0 dBm. The quartile chart shows that TPP nodes barely try lowering their transmission power and converge on the maximum. In addition, ACTOR improves the average number of retransmissions for all of the nodes in the network. This metric depends on (i) the number of hops and (ii) single-hop contention. Since the number of hops has not changed, a higher number of retransmissions indicates more hidden terminals for the medium in the MAC layer. We can see that ACTOR succeeds in reducing the hidden terminals. In addition to the transmission power, another popular best practice to reduce energy consumption is to reduce idle listening by allowing the node to put the radio in sleep mode [42]. Although the results presented here considered CSMA, ACTOR is expected to be beneficial for other MAC protocols as well. For example, TSCH networks take advantage of diversity in both the frequency and time domains. TSCH nodes agree on a schedule to use channels in time (time is divided into timeslots). These schedules contain shared timeslots for broadcasts, reserved timeslots for unicast communications between pairs, and also idle timeslots for the radio to sleep. The scheduler needs to take the interfering nodes into account when assigning reserved slots. Optimizing the transmission power leads to fewer interfering nodes and fewer constraints for the scheduler. However, transmission power control in a duty cycling network is considered out of the scope of this work.