# A Power Planning Algorithm Based on RPL for AMI Wireless Sensor Networks
## 6 Conclusions  
This paper presented a transmission power planning method for DODAG topologies suitable to AMI networks. The study shows that it is possible to control the transmission power of nodes in RPL networks to provide more stable and resilient topologies. Without changing the protocol, the proposed method induces RPL built DODAGs where parent sets possess a minimum preset size, which allows the design of networks with a desired degree of resilience. The method also induces the construction of DODAGS where the links connecting nodes to their parents all have a similar quality, allowing the nodes in the parent set to offer connectivity through paths of similar quality. Besides the clear advantage of providing a more stable network, this approach improves the RPL performance because the rank of a node becomes a closer indication of the path cost to the root through this node.  
Our algorithm has been evaluated in two distinct channel conditions: rural and urban areas. The findings show that the method is very promising because it is able to achieve the goals of resilience and stability and still maintain a good average cost of preferred paths in the urban setting, and better average costs in the rural setting. With respect to the latter aspect, the performance of our method is best for networks with poorly connected topology, which occurs when the distances between neighboring nodes are very variable. In this case, the quality of the links is worse and our algorithm has more room to make adjustments to improve results. For the rural scenario, which has this characteristic, it was shown that the algorithm is able to find paths through preferential parents with lower costs.  
The interference between network nodes is not addressed in our study because this issue can be solved by assigning non-interfering transmission channels to nodes belonging to the same interference domain, i.e., using channels at distinct frequencies or non-overlapping time slots. However, to assure that the comparisons made in Section 5 are fair, we perform the evaluation with all methods spending the same amount of energy, thus subject to equivalent levels of interference. The interference of external resources is also not part of the scope of our study because this problem can be handled by the RPL, as discussed in the Section 1.  
Figure 10: Power planning example.  
It should be noted that the mechanisms and algorithms presented can be used for other applications that require structured networks for which energy consumption is not a primary requirement. Many of the networks used in applications for smart cities may fit into this context.  
In Section 4.1, we have provided comments on how the proposed algorithm could be used in a centralized communication architecture. In our future studies, we intend to specify an architecture based on SDN to support the centralized operation of the proposed algorithm.  
This work has been partially supported by CNPq (Brazil).  
**Author Contributions:** [PERSON] and [PERSON] conceived and designed the centralized operation of the algorithm; [PERSON] and [PERSON] conceived and designed the power adjustment algorithm and performed the experiments; [PERSON] and [PERSON] conceived the theoretical model and designed the experiments.  
**Conflicts of Interest:** The authors declare no conflict of interest.