# A Survey on Congestion Control for RPL-Based Wireless Sensor Networks
## 5 Discussion  
In this section, we suggest future research challenges. **Efforts to reduce resource consumption. ** In designing protocols for LLNs, energy consumption is one of the major considerations. Most schemes reviewed aim to conserve energy directly or indirectly. Limited memory capacity also has been a critical constraint. Showing the memory requirements in RPL implementations of Contiki OS and TinyOS, [PERSON] et al. point out that RPL has too large a memory footprint for resource-constrained devices [6]. However, the recent emergence of more powerful sensor motes indicates that the resource constraints in LLNs are changing. Developing Hamilton, an open source, 32-bit SoC-based mote, [PERSON] et al. suggested new directions for the system architecture for networked sensors in the post-SoC era [55]. The authors also present the paradigm shifts to be considered in designing low-power network protocols. Among them, the issues closely related to RPL design are as follows. First, it has been pointed out that since protocol standards are not completely implemented due to resource constraints, devices using different implementations may not interoperate. As low-power 32-bit SoCsare becoming more capable and have more memory space, it may be feasible to implement the whole RPL standard, which will lead to better interoperability between devices. Second, the advanced radio features give new research opportunities such as adaptive data rate control, interference avoidance, and multiantenna diversity. Also, it should be considered that post-SoC notes have a different pattern of power consumption from the traditional motes in the sense that both the MCU and the radio become comparable power consumers in post SoC notes. **Investigation via real implementation and experiments. ** [PERSON] et al. highlight the importance of evaluation through experiments using implementations on real embedded devices throughout their survey [7]. They point out that more than half of the research publications reviewed evaluated their proposals through simulation only, rather than with experiments on real testbeds. Our survey shows a statistic supporting their argument. Out of 23 publications reviewed in Section 4, only seven schemes evaluated performance using experiments on testbeds. **Considerations on multiple RPL instances. ** RPL allows an LLN to have multiple RPL instances with different QoS requirements. Each instance may have a different OF which uses different routing metrics and constraints. [PERSON] et al. state that the statistics on the research papers from 2010 to 2016 indicate a lack of studies on multiple instances [7]. To the best of our knowledge, there are still a handful of studies on congestion control in an environment with multiple RPL instances. Most of the efforts to apply multiple instances have been focused on smart grid (SG) environments where applications are heterogeneous in terms of QoS requirements. RFC 8036 on applicability of RPL in AMI (advanced metering infrastructure) networks states that multiple RPL instances can be supported in multiservice networks where different applications may require the use of different routing metrics and constraints, e.g., a network carrying both smart metering data (SMD) and distribution automation (DA) traffic [56]. [PERSON] et al. proposed an RPL extension, RPL-M, for a smart grid neighbor area network (SG NAN) which is expected to carry a mix of both periodic and critical traffic [57]. To differentiate QoS requirements at the network layer, RPL-M exploits multiple instances which use a hop count for periodic traffic and ETX for critical traffic. Pointing out that performance of RPL-M was evaluated in 802.11b networks, [PERSON] et al. showed that multiple RPL instances can improve PDR and latency of each type of traffic in 802.15.4 networks [58]. More recently, [PERSON] et al. proposed an objective function, OFQS, with a tunable multiobjective metric, mOFQS, that is a composite metric of ETX, the delay between two nodes, and the remaining energy [59].