The RPL is a dedicated protocol for resource-constrained IoT networks. In most OFs explored, only one routing metric is considered either reliability or resource availability of parent nodes. Considering only reliability (ETX), the RPL routing may tend to unbalance energy distribution among nodes. On the other hand, considering only the energy consumption without considering the reliability of links, several data packets may be lost. Moreover, if a node has already selected a parent, another node has a better rank value than its parent. Instead of changing its parent node, a node estimates the difference between the rank of the new candidate and the minimum rank value.
If the difference value is not greater than the pre-set threshold, the node still uses its current preferred parent. It is named hysteresis. However, most of the objective functions do not reflect the network situation promptly due to hysteresis and load imbalancing. It is essential to modify the OF in RPL by considering and balancing both the energy consumption and packet loss even under a large-scale network. Several heuristic algorithms can be used to improve the efficiency of RPL routing. Among them, the Chaotic genetic algorithm effectively combines multiple metrics using weighting factors as per the network situation and improves the routing performance.