## 7 Conclusions and Future Work  
Due to advances in semiconductor manufacturing, off-the-shelf devices with multiple radios have become common and affordable. At the same time, the most commonly used routing protocol in WSNs (i.e., RPL) is known to be susceptible to external stressors such as jamming and interference. To remedy this, we adapted RPL to exploit the capabilities of modern multi-interfaced devices. That is, we developed a new RPL OF called DRiPLOF, and compared its performance with single-interface solutions (low- and high-rate MRHOF) and a state-of-the-art multi-interface approach (POOF). To analyze the performance of our solution, we simulated a network wherein devices have a long-range/low-throughput 868 MHz radio and a short-range/high-throughput 2.4 GHz radio. In absence of jamming, DRiPLOF had negligible overhead compared to a single-interface alternative with optimal radio selection, yet it can adapt when a different radio type is more appropriate. When jamming was introduced, only DRiPLOF could maintain a stable network. Hence, it significantly outperformed all competitors, realizing stable end-to-end delivery rates exceeding 90% compared to a median 65% for the considerably less stable closest alternative (POOF). Overall, this makes DRiPLOF an excellent candidate for adoption by RPL networks: (1) expecting to suffer interference from, e.g., competing technologies such as WiFi(tm) (in the 2.4 GHz band) and LoRaWAN(tm) (in sub-GHz bands); and (2) that are to be deployed in unknown conditions, meaning you cannot select the best radio technology a priori. Nonetheless, future research efforts may yet improve upon our solution. For example, we assumed all devices had the same set of interfaces. However, one could devise a mechanism through which all nodes know which interfaces/how many they should possess. This would allow, e.g., nodes with a less-than-nominal amount of interfaces to join the network as well. Like [PERSON] et al. (2018), we could also support multiple PHY configurations per interface instead of just multiple single-PHY interfaces. However, this requires a synchronized MAC protocol (e.g., TSCH) because a node would need to know when its neighbor can receive over a certain interface with a given PHY configuration. With one PHY configuration per interface, this was not necessary as long as all interfaces were always-on. Finally, it would be interesting to see if basing preferred interface selection on more than the \"best metric\" could result in, e.g., an equally stable, but even more energy-efficient network (in certain circumstances). This might be achieved by combining  
Figure 10: Simulation results for the conditions involving a jammer. (**a**) The end-to-end latency of upward data packets successfully received by the root. (**b**) The number of times a non-root node changed its preferred parent. (**c**) The ratio of data packets processed by the root to the number of \(T_{s}\) expiration events. (**d**) The time spent (by a non-root node) detached from the DODAG. multiple metrics for every interface (presumably prior to preferred interface selection), possibly with some sort of metric-weighting system, which in turn may or may not use some form of machine learning. **Supplementary Materials:** The full code base (including instructions) and curated data files are available online at [[https://www.mdpi.com/article/10.3390/s22103906/s1](https://www.mdpi.com/article/10.3390/s22103906/s1)]([https://www.mdpi.com/article/10.3390/s22103906/s1](https://www.mdpi.com/article/10.3390/s22103906/s1)). **Author Contributions:** Conceptualization, R.E., E.D.P., and J.H. ; methodology, R.E. ; software, R.E. ; validation, R.E. ; formal analysis, R.E. ; investigation, R.E. ; data curation, R.E. ; writing--original draft preparation, R.E. ; writing--review and editing, R.E., E.D.P., and J.H. ; visualization, R.E. ; supervision, E.D.P. ; project administration, R.E. and E.D.P. ; funding acquisition, R.E. All authors have read and agreed to the published version of this manuscript.