## 5 Analysis of the Results  
As mentioned in the formulation of the problem, the model contemplates two restrictions: capacity and range. Capacity establishes the number of devices that each node can conglomerate, while the range establishes the length in meters that the nodes have as a distance limit to connect. In addition, to determine the performance of the model, six scenarios are proposed according to the ranges of 50, 75, 100, 200, 300, and 1000 m that can be tested at the candidate site; in each scenario, six finite numbers of capacity are tested, generating 36 results that will allow analyzing and determining the optimal solution for the site. From the allocation of weights, it is established that the smart meters have the possibility of connecting to generate multi hops or connect with the UDAP to establish communication with the data applicant or otherwise to receive data from the CO. On the other hand, the UDAP are required to connect with the meters and generate multi hops, which implies that their first wireless technology should consider mesh connections; the UDAP should also connect with the BS through cellular technology in their last mile. Therefore, the result is a concentrator with double technology to establish links between the supply and demand entities of the electric system. Therefore, the model has been restricted to 4 hops, and the weights for the construction of the MST have been detailed in the Algorithm 3. It is also established that the UDAP cannot connect directly with the central offices since the base station is the one in charge of communicating them through the Internet, so its weight will be assigned so that the slogan is fulfilled. It is also necessary to mention that based on performance studies conducted by other researchers, a large capacity in terms of devices per node requires more time to achieve an adequate transmission probability,in addition to working with the specifications guaranteed by the manufacturers, so for this study, it is established capacities of 5, 10, 15, 20, 25 and up to 30 users per node to generate the tests. The result of the number of users per concentrator concerning the optimal number of UDAPs can be seen in Figure 3, where it can be observed that the minimum number of optimized concentrators is 9, taking into account that the initial number was 50 and that for this result each UDAP can host up to 30 devices. Of the six ranges defined above, the results with range parameters greater than or equal to 200 m do not show changes. Therefore the program confirms that even if the range length increases, whatever the capacity is, the solution becomes invariant. It is verified that the capacity restricts the problem. However, for the candidate site and the number of devices established beyond a specific range, it is impossible to obtain better results. Similarly, it can be seen that in the scenario with a range parameter of 50 m, the minimum number of concentrators is not reduced to less than 32 UDAPs, even if the capacity is modified, which also makes it clear that in this case, the solution is invariant from a capacity of 10 users per node. This graph also shows that the optimization model. In addition, the minimization of the UDAPs is evident for the constraints established in each of the 36 trials performed. In the Figure 4, is verified that in the proposed candidate site, Greedy SCP shows that with ranges of 50 m, it is not possible to connect all the devices in the network, while from 75 m of range, it is possible to ensure coverage of all the meters if the capacity restriction is greater than or equal to 15. As a result, a range of 50 m or less is applied as a restriction; it will be challenging to establish routes with some devices. So it must be found that some nodes will be outside the tree built for the topology of the network. The number of concentrators is reduced, and the model guarantees the construction of a tree with all network devices.