## 4 Energy Aware Software Defined Network (EASDN) Routing Algorithm
In Figure 13a, we can see the energy consumption per bit of an EASDN is 2.6919 \(\times\) 10\({}^{-7}\) whereas a traditional SDN and AODV consume 2.7949 \(\times\) 10\({}^{-7}\) and 4.7993 \(\times\) 10\({}^{-7}\), respectively. In the second scenario, the EASDN energy consumption per bit is also lower than a traditional SDN and AODV as shown in Figure 13b. The description is similar to the one above for the first scenario. In Figure 14, we compared the network alive nodes with different algorithms. Here we used only the second definition of life time (e.g., the time until the last node runs out of energy.) As shown in

Figure 13: Energy consumption. Figure 14, an EASDN algorithm has more number of rounds than traditional a SDN and AODV. An EASDN is an energy aware algorithm. It changes the path of the forwarder node when it observes any node has less energy when compared to neighbor nodes, so it manages the network concerning residual energy. However, in a traditional SDN, it could not balance the energy consumptiondue to the fixed pathand it also uses only short distances for establishing the routing path. Therefore, it may use the forwarder node which has a low residual energy when compared to the neighboring node that leads to disconnect the underlying nodes. In an AODV, it uses the hop count for establishing the path, but the AODV could not provide the optimal hop count because it does not have a global view and sometimes the hop count is higher, which leads to consuming more energy. As shown in Figure 14, when the EASDN algorithm is implemented, it gives more than 14,000 rounds however in other traditional SDN and AODV algorithms, they give approximately 12,000 and 6000 rounds. In the second scenario, when the area dimension is smaller, each algorithm gives a number of rounds as shown in Figure 14 that also show a similar behavior described in the first scenario. Figure 15 shows the average delay comparison between our proposed algorithm and a traditional SDN and AODV. The proposed algorithm gives a better performance in terms of average delay because it does not use the broadcasting to develop the routing path like in the AODV. In the AODV, each node uses the broadcasting, which takes a long time for establishing the path. Sometimes it chooses a long path in terms of distance because it counts the least number of hops even if the distance between the two nodes is too large therefore, it leads to increase the transmission time from source to destination. Figure 14: Alive nodes vs number of rounds. As shown in Figure 15, the proposed algorithm has 193 ms average delay where the traditional SDN and AODV have 212 ms and 548 ms, respectively. ## 6 Conclusions and Future Work

SDN-enabled WSN provides a dynamic, flexible, and easy to manage paradigm to revolutionize the traditional WSN. Consequently, in this paper we utilized the SDN potential to reduce energy consumption in a WSN by proposing an energy efficient routing protocol. The main purpose of the proposed protocol was to increase network lifetime. The proposed scheme was implemented in a real environment. The evaluation results show that an EASDN enhanced network lifetime from 18% to 22% in comparison to a traditional SDN and AODV. Moreover, it also decreased the average delay and improved packet delivery ratio. In future, we intend to implement and evaluate the proposed scheme on a large scale scenario using a simulations. We also plan to implement the machine learning based routing algorithm for optimizing the energy consumption of network nodes to enhance the network lifetime. [PERSON] proposed the routing algorithm, performed the real-time experimental work and wrote the manuscript. [PERSON] provided the guidance during experiments, verified the results and proofread the manuscript. [PERSON] refined the manuscript and provided valuable comments. This research was supported by the Brain Korea 21 Plus Program (No.