# A Novel RPL Algorithm Based on Chaotic Genetic Algorithm
## 2 Overview and Problems of RPL
### Problems  
At present, it has been pointed out that network performance can be improved by constructing different composite metrics. In Ref. [13], authors proposed the minimum rank rule, which means that in the candidate parents set (neighbor set), the candidate parent with the minimum rank value will be selected as the preferred parent (the next hop). But the routing metrics proposed in [16] were not considered. Moreover, the minimum rank rule does not perform any load balancing operations, which may affect the network performances to some extent. In Ref. [15], [PERSON] and [PERSON] put forward MRHOF, a kind of OF that decides routes according to minimum routing metric rules, while employing hysteresis to decrease disturbance (avoid changing the preferred parent frequently) in response to small routing metric value changes. In other words, MRHOF decides routes based on the following two rules:  
1. Node chooses the candidate parent with smallest path cost as preferred parent;
2. If one node already selected a preferred parent but there is another candidate parent with the minimum path costing less than the selected preferred parent, then before changing its preferred parent, the node shall first compare the difference value of path cost between the minimum path cost candidate parent and the selected preferred parent. Then, if the difference value is greater than the pre-set threshold, the node chooses this minimum path cost candidate parent as its new preferred parent. Otherwise, the node still uses its current preferred parent. This is the so called \"hysteresis\". However, MRHOF cannot reflect the network situation in a timely manner due to \"hysteresis\" and without load balancing. In Ref. [17], the authors put forward the hybrid routing metrics to improve the network performance. The proposed hybrid routing metric includes lexical and additive methods. In the lexical approach, the node chooses the preferred parent according to the following rules: the neighbor (candidate parent) with the maximum or minimum value of the first referential routing metric should be chosen as the preferred parent, while if there are two or more candidate parents having the same minimum or maximum value of this first referential routing metric, the second referential routing metric should be used (use the same rules as the first referential routing metric). In the additive approach, several routing metrics and their relative weighting factors are combined in an additive \begin{table}
\begin{tabular}{l l} \hline \hline
**ICMPV6 Control Messages** & **Functions** \\ \hline DAO (Destination Advertisement Object) & Transmitting destination address information and \\  & constructing upward routes \\ \hline DIO (DODAG Information Object) & Containing some information that used to detect RPL \\  & Instance, obtain relevant configuration parameters, \\  & select candidate parent set, maintaining DODAG, etc. \\ \hline DIS (DODAG Information Solicitation) & soliciting DIOs from neighbors in LLNs \\ \hline DAO-ACK (Destination Advertisement Object & Informing DAO sender that DAO has been received \\ Acknowledgement) & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: ICMPV6 control messages used in RPL. manner to form a composite function which is used to select the preferred parent. The weighting factors in composite function may be altered to focus on the corresponding metrics. However, the lexical way often cannot make all referential routing metrics valid. Since there are two or more candidate parents with the same minimum or maximum value of the first referential routing metric, the second referential metric takes effect; however, this circumstance--let alone the third or other subsequent routing metrics--rarely occurs.. Furthermore, the additive way has no definite weighting factors distribution theory analysis and basis. The determination of the weighting factor of each metric is mainly based on experts' personal experiences.