# Logically-Centralized SDN-Based NDN Strategies for Wireless Mesh Smart-City Networks +
## 4 Experimental Evaluation
### Scenario 2--Evaluation of the Proactive Strategy  
In scenario 2, we aim at the effectiveness of the SDN-based proactive procedure in terms of NDN performance over WMN smart-city environments. We use a multi-hop network topology consisting of ten wireless network nodes as illustrated in Figure 9 with green circles, including one Consumer (Node10-29) and one Producer node (Node10-20), located at the edges of the network. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**NDN Path** & **Low TP (5 dBm)** & **High TP (10 dBm)** & **Unstable TP (5–10 dBm)** \\ \hline Path 1 & 41 & 1186 & 362 \\ \hline Path 2 & 1469 & 314 & 1138 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Reactive’s solution path choices over 1500 interest-data exchanges. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**NDN Path** & **Low TP (5 dBm)** & **High TP (10 dBm)** & **Unstable TP (5–10 dBm)** \\ \hline Fixed Path1 & 61.62 & 29.86 & 53.71 \\ \hline Fixed Path2 & 45.36 & 38.62 & 43.35 \\ \hline Reactive solution & 48.58 & 29.93 & 48.99 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Average of Interest-Data exchanges performance delay (msec). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**NDN Path** & **Low TP (5 dBm)** & **High TP (10 dBm)** & **Unstable TP (5–10 dBm)** \\ \hline Fixed Path1 & 115 & 11 & 61 \\ \hline Fixed Path2 & 70 & 53 & 58 \\ \hline Reactive solution & 58 & 40 & 51 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Total amount of failures over 1500 interest-data exchanges. First, we discuss the clustering results over the experimental network topology. More precisely, the proposed clustering technique considers 4 clusters, classified from best to worst based on their intra-cluster mean value; the best cluster provides the minimum intra-cluster mean value. Figures 10-12 illustrate the clustering outputs considering as inputs the absolute RSSI, the delay, and the bivariate RSSI-delay values of the links, respectively. The color gradations denote the cluster that each link belongs to, i.e., green, blue, black, and red colors symbolize the clusters from the best to worst, respectively. According to the clustering results: (i) RSSI values mainly depict the distance among the nodes; as expected, since we experiment over an indoor environment with low interference, (ii) no evidence for the high similarity between RSSI and delay values exists, e.g., the path from node-1 to node-20, (iii) RSSI-delay-based clustering presents dissimilarities from both RSSI and Delay clustering. The second part of this scenario includes: (i) the performance evaluation of the available NDN paths over the considered WMN and (ii) the comparison of the clustering results with the choices of our dynamic SDN-based solutions. Specifically, in this phase, we  
Figure 10: RSSI clustering results among network nodes. Figure 9: Selected topology—w-iLab.1 office lab 10 th floor [38]. performed 15,000 Interest-data exchanges (using the reactive process) over the topology described in Figure 5, and we recorded the BATMAN path choices (i.e., which paths have been chosen and how many times). Then, we performed 1500 Interest-data exchanges and 100 file transfers for each selected path using the NDN chunk method, and finally, for each path, we present the clustering results. Table 5 enlists: (i) the reactive's solution selected paths out of a total of 15,000 interest-data exchanges (Paths); (ii) the hops number of each path (Hops); (iii) the times each path was chosen during the experiment (reactive's solution path choices); (iv) the average delay for the Interest-Data exchanges (Interest-Data); (v) the percentage of Interest-Data exchange failures (Fails %), and (vi) the clustering results, for the metrics under consideration, i.e., RSSI, Delay, and RSSI-Delay. Here, notation C.i, \(i=\{1,2,3,4\}\) refers to paths sorted from best to worst. A path is characterized by its worst link, for example, C.1 exclusively includes the best links in terms of clustering and C.4 includes at least one link estimated as the worst link.