# Logically-Centralized SDN-Based NDN Strategies for Wireless Mesh Smart-City Networks +
## 4 Experimental Evaluation
### Scenario 1--Evaluation of the Reactive Processes
Note that the significant difference between \(RTT_{NDN_{p}}\) and \(RTT_{NDN_{c}}\) (\(\approx\)87 msec) is attributed to the locally occurred cache hits in the Consumer node (without requiring any network transmission) while fetching data from the remote Producer requires interest and data packet transmissions over the 3-hop topology. Figure 7 illustrates the average best paths hops and the total _Best Path Changes (BPC)_, per round (experiment repetition). As is shown, the average number of hops (in each round) is 3, confirming the validity of the experimental methodology. Additionally, the _Best Path Changes_ deviation (i.e., ranging from 7 to 19) illustrates the wireless links volatility of the test-bed's setup and highlights the proposed system's capability to capture frequent network changes and establish the appropriate paths. Figure 5: WMN topology, considering the 9 th floor of the w-iLab.1 test. Figure 6: Average \(RTT_{NDN_{L}}\), \(RTT_{NDN_{p}}\) and _Total Delay_. Subsequently, we discuss the outputs of the reactive process, targeting the effectiveness of NDN end-to-end communication, and, therefore, we exclude in-network caching (i.e., NDN cash contents). Here, the network topology consists of 6 network nodes from the 10 th floor of the w-iLab.1 Fed4 FIRE+ test-bed, as it is depicted in Figure 8. Node10-29 hosts the Consumer, node10-20 the Producer, and Node10-32 the Controller, which (as in the previous experiment) belongs to the same wireless topology. According to Figure 8, two multihop paths may be formed for the end-to-end communication, i.e., path1 (node10-29, node10-9 and node10-20) and path2 (node10-29, node10-32, node10-34, node10-5 and node10-20). The Transmission Power (TP) of node10-34 and node10-5 is 10 dBm, and the TP of node10-32, node10-9, and node10-29 is 5 dBm. Finally, we consider three types of communication conditions, by adjusting the Producer's TP, as follows: (i) 5 dBm (low TP), (ii) 10 dBm (high TP), and (iii) periodically increase/decrease from 5 dBm to 10 dBm, every 5 minutes (unstable TP). Next, in Tables 2 and 3, we compare the proposed SDN, BATMAN-based, reactive solution with the conventional NDN approach, i.e., fixed path1 and path2 solutions, over the total amount of 1500 Interest-Data exchanges from the NDN Consumer node. Table 2 enlists the average delay (msec) values of the Interest-Data exchanges for the fixed NDN paths and the reactive NDN solution. According to the outputs, Path2 provides the lower delay values for both low and unstable TP of the Producer, on the contrary, Path1 minimizes the delay for the case of high TP. Regarding the results of the proposed reactive strategy, the integration of the BATMAN protocol provides comparable performance in all  
Figure 8: WMN topology, considering the 10 th floor of the w-iLab.1 test-bed. Figure 7: Number of Hops and _Best Path Changes (BPC)_ pers round. cases, implying that a dynamic approach can successfully select the best paths, according to the network conditions. Similarly, in Table 3, we evaluate the fixed and dynamic NDN path selection solutions in terms of reliability, i.e., comparing the total amount of Interest-Data exchange failures. The reactive strategy demonstrates its effectiveness in challenging communication conditions (low and unstable TP), providing the lowest number of interest-data failures, and also, indicating the potential gains of a dynamic mechanism, concerning unstable communication conditions. On the other hand, Path1 has the least failures in high TP cases. Finally, Table 4 presents the results of the reactive solution's path choices regarding path 1 and path 2 (i.e., how many times BATMAN chose each path), considering the different TP adjustments for the Producer node. As it is shown, the reactive solution's path choices are in accordance with the best path selection, derived in Tables 2 and 3. In other words, our dynamic approach, integrating the functionality of NDN with the decisions of a wireless mesh protocol (i.e., BATMAN), successfully detects the best paths.