# A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic
## 2 Related Works  
In recent years, various routing protocols have been designed to take the importance of determining the path towards a destination for a communication network into account. In general, these protocols have been specifically designed for specific network environments and applications. RPL was standardized for 6 LoWPAN networks bringing the concept of IoT into real life. Since then, many studies have evaluated the performance of RPL and they have suggested some improvements to potential shortcomings and open issues [13; 14]. In the literature, many research works have carried out on various aspects of RPL based wireless sensor networks (WSNs), such as load balancing, energy conservation, QoS support, and protocol optimization [15]. However, context awareness in the LLN based IoT network is still a broadly unexplored research area. While RPL has substantially satisfied LLN's requirements for traditional WSN based applications, some subjects, such as context-aware routing to support IoT based smart city application requirements, are open for improvement. Many efforts have been made to design the objective function of RPL [16] while using a composite routing metric to meet routing requirements in a diverse application domain. The proposed OF enhancements differ in such a way that how they combine multiple metrics. Several mechanisms are adopted to combine the respective metrics. Some of the widely adopted mechanisms of metric composition are additive and lexical. [17]. However, all of them have positive and negative aspects. We have summarized the work that is focused on improving the RPL OFs while using the various metric composition techniques. The Taxonomy of objective function enhancements is as shown in Figure 1.  
Topology construction and path selection in the RPL protocol is performed based on the OF. OF defines how a node calculates its rank and how to combine different metrics and constraints during the rank calculation process. However, the RPL specification [5] does not obligate using a specific objective function or set of rules. Therefore, you can achieve the specific application objective by manipulating the default objective function and its parameters. This flexibility allows for choosing different routing metrics during OF design, but combining the multiple metrics is not that easy. In [9], IETF RFC 6551 has presented a set of routing metrics and constraints used in OF, but it has not explained how to combine them. Therefore, it is the designer who makes the ultimate decision regarding which metrics to select or how to combine them into OF. Different implementations of RPL use different metrics, such as ETX, hop count, or a combination of both. For instance, the Contiki RPL implemented by Contiki OS uses MRHOF as the default OF and also implements OF0. As a result, in RPL scope, designing OFs according to the application and network needs is still an open issue. In [18], the authors have presented hybrid (additive and lexical) composition mechanisms, which combines two routing metrics in order to optimize the network performance. The authors design primary metrics that capture network characteristics and holds the monotonicity property to build composite metrics to ensure varied application requirements. In the additive method, different metrics and their respective weights are combined in an additive manner to build a composite function, where the two components must maintain the same ordering relationship to ensure the validity of the composite metric. However, in a lexical approach, such strict order relation is not required. Unlike the additive approach, the lexical combination method provides clear prioritization of metrics. While using a lexical approach, a node selects the preferred parent that is based on the maximum or minimum value of the first referential routing metric. However, not all referential routing metrics can be made valid using this approach.