# A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic
## 2 Related Works
Although this metric combination mechanism ensures better routing performance in large scale network, it is unclear that, in heterogeneous network scenarios, like smart city, how it addresses the resource constraints issue with SIGMA-ETX metric. Another key issue with this approach is that the monotonicity property of the rank calculation. The SIGMA-ETX metric might violate this property, which results in a high risk of loop formation in the network. The fuzzy logic-based RPL objective functions have also been presented in some studies. The authors in [24] highlighted that the combination of only two routing metrics might be unable to fulfill the requirement of the multi-purpose network as the network might have different applications with different performance objectives. To deal with this matter, the authors point out the comprehensive objective function should be designed that combine multiple routing metrics to optimize different application requirements. To achieve this goal, the authors presented a new QoS-aware fuzzy logic-based objective function, called OF-FL. It works with fuzzy logic and forms a configurable routing scheme while using fuzzy parameters. Similar to other OF, a node that receives a DIO message executes the fuzzy process to compute the rank. OF-FL incorporates four different routing metrics such as link quality, hop count, end-to-end delay, and node energy, to optimize the parent selection process. OF-FL considers various network aspects during the route construction phase. In [25], the authors present a fuzzy sets-based cluster RPL called FC-RPL to prolong the network lifetime. FC-RPL operation has three different subsequent phases, the cluster formation phase, cluster head selection phase, and cluster head parent selection phase. Based on the Euclidean distance, the clusters are formed. To select the cluster head for each cluster, it applies the fuzzy set to three metrics, such as centrality, number of neighbors, and residual energy. A similar fuzzy-based approach for energy efficiency in LLN is presented in [26]. The authors propose fuzzy logic based energy aware routing protocol, called FLEA-RPL. It includes three routing metrics, ETX, Load, and residual energy (RER), to select the best path towards the root for efficient data delivery. Another similar fuzzy logic based method for combining the different routing metrics is proposed in [27]. Unlike [24; 25; 26], the proposed fuzzy inference method has adopted the two-stage fuzzy process and it includes three routing metrics, namely energy, delay, and ETX. The first stage of the fuzzy process combines both ETX and delay metrics in order to compute QoS. Later, this QoS value is taken as input for the next stage of the fuzzy process and combined with the energy metric. Another similar fuzzy based approach has been followed in [28]. The authors in [29] also adopted a similar fuzzy process to design multiple objective functions for RPL. Four different OFs are designed to use in one application. According to the requirements of the application, these objective functions are substituted to construct the DODAG. Dynamically changing the OFs is based on the context of the application. To classify the best route using fuzzy logic rules, it uses three routing metrics that is the number of hops (NH), energy consumed (EC), and ETX. All of these metrics that are used in four different OFs are specified in the default RPL specification and are based on the application requirements, these metrics are classified, and prioritize accordingly. In addition, out of the four proposed OFs, only one objective function (DQCA-OF4) combines all three metrics in order to classify the best route. It indicates that other OFs might not ensure the decision making of the best route because fuzzy inference system requires three input variables (NH, EC, and ETX) to estimate the degree of quality of the routes. In terms of a fuzzy process and context-based information, this approach is close to our proposal. However, some design characteristic of RPL is distinct in our proposition.