# A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic
## 2 Related Works
For instance, we use a single objective function in one RPL Instance. Adopting multiple OFs in single RPL Instance might not be a viable approach for heterogeneous network [5; 15]. Besides, the routing metrics that were considered by these two fuzzy-based systems are not the same. Unlike [29], COOF proposes a new RPL compliant routing metric called queue fluctuation index (QFI). Another metric, called the residual energy index (REI), is defined in a way that it indicates the status of residual energy of nodes recursively. Both of the metrics are representative of the node's resource availability, and their information is carried as node state object and energy object, respectively, in the DIO message. The common metric used by both the fuzzy system is ETX. However, we obtain the average ETX by using a sliding window-based averaging method. Using four different OFs in a single RPL Instance may result in more latency, especially in the heterogeneous network and it may not work effectively in emergency response application of smart city vision. There are also some other enhancements on RPL objective functions, in which metric composition is based on Game Theory [30] and MCDM [31]. These improvements are basically for congestion control in LLNs. Different routing metrics are used to calculate the rank of a node in a network. Each child node uses a potential game theory-based strategy to select the best parent. Similarly, the parent selection process can be developed as a multi-criteria decision making (MCDM) problem by combining different routing metrics. In the IoT paradigm, context-aware communication is a salient technique that enables intelligent interactions between applications and devices [32]. Context awareness is a process in which context information is treated as an evaluation attributes. As described in [32], these contexts can be divided into several groups of awareness, such as resource state, information, privacy, QoS, and mobility. Moreover, context can be used to determine what services and information need to be presented to the user. Many research papers in the literature concentrate on efforts to deal with the issue of context-sensitivity of IoT applications [33]. In regards to context awareness, the authors in [34] have proposed a scalable context-aware objective function (SCAOF) that adapts the RPL for the environmental monitoring in the agricultural sector with contextual facts. It is designed according to the composite routing metrics approach by combining the reliability-aware, robustness-aware, resource-aware, and energy-aware contexts. The testbed experiments confirm that SCAOF can prolong network lifetime as well as improve the QoS of agriculture-oriented applications. However, each node running SCAOF has to pass a relatively large number of parameters in the DIO message header, which increases the risk of layer-2 fragmentation. This obligation makes resource-constraint devices prone to resource depletion. However, most of the above-mentioned objective function enhancements does not consider the context awareness in RPL routing mechanism. Communicating with a set of IoT devices that share the context is essential in smart city vision. In this backdrop, context-sensitive computing is now considered to be an important component of IoT, so it has become more relevant in the research community and market. It is because context-sensitive systems can adjust behavior to the current situation without user's intervention. This relevance motivated the authors to suggest the state-of-art approach to improving the RPL. Furthermore, SCAOF takes into account the composite routing metrics approach in the path selection process; therefore, we include it in the comparative analysis that was performed in this work along with RPL.