## 7 Conclusions  
We proposed an adaptive beamforming time with round-robin MAC approach with the goal to improve benefits in terms of energy consumption introduced by the employment of round-robin scheduling in directional antenna MANET contexts [24]. This work has been mainly motivated by the fact that, although an round-robin approach is able to counteract main directional antenna issues that can usually occur at the MAC layer, the energy consumption distribution is not well distributed among sectors. Basically, the unbalanced energy distribution, due to problems introduced by round-robin such as the time slice and queue issues, promotes a non-negligible waste of energy that can limit the overall network performance, especially in terms of packet delivery ratio. In order to attempt to mitigate these problems, we proposed a solution that aims to eliminate the static assignment of the beamforming (or sector) time for sectors that could bing about a non-efficient energy distribution among sectors. The presented solution provides a dynamic assignment of the beamforming time by considering the current size of the sector queues and the average beamforming time; all parameters are updated periodically. The main advantage of that dynamic assignment is that, when data traffic is unbalanced in the simulation scenario, the slower a certain sector is to empty its queue (that is directly related to the size of the queue), the higher the quantum of time assigned to that sector is. The ABT-RRMAC has been compared to the classic omnidirectional MAC exploiting the round-robin principle and with the RR-MAC presented in [23, 24] that uses SASs instead of omnidirectional antennas. Results, in terms of the energy consumption of nodes, by considering different configuration cases related to the number of sectors, show our ABT-RRMAC is able to reduce the maximum energy consumption amount per sector by about 37% on average, with respect to RR-MAC, and even 50% compared with the omnidirectional case. Furthermore, our proposed approach helps to level the energy consumption of nodes by uniformly distributing the total amount among sectors. For a further investigation, the PDR of all considered cases was evaluated as a function of the number of sectors and queue size; with reference to queue size, ABT-RRMAC provides for a minimum PDR of 0.84, which considerably improves the value of 0.72 obtained in RR-MAC. This result is significant because the dependency of the PDR is reduced with queue size. Finally, our approach has been evaluated in terms of energy consumption by considering the mobility of nodes; in this regard, results show that ABT-RRMAC outperforms RR-MAC; this trend remains almost uniform independently from the size of the queues. Lastly, in order to evaluate our contribution with respect to the current state of the art, we implemented and analyzed the DA-MAC protocol and compared it with our proposal. Results show that DA-MAC is quite similar to ABT-RRMAC in terms of PDR if the number of nodes in the network is limited; our protocol tends to outsail DA-MAC as the number of nodes increases. The same trend is reflected with regard to the energy consumption of nodes in which a difference in terms of wasted energy occurs between DA-MAC and our proposed approach; in this respect, ABT-RRMAC preserves more energy compared to DA-MAC mainly because of the relatively small number of operations performed.  
Figure 13: Energy consumption.  
The Table 3 summarizes the list of symbols used in the manuscript:  
**Author Contributions:** [PERSON] contributed to most of the formulations and simulations and implemented the proposed model under the supervision of [PERSON] and [PERSON]; [PERSON] was responsible for data curation and results validation and helped revise the paper.  
**Funding:** This research received no external funding  
**Conflicts of Interest:** The authors declare no conflict of interest.