# A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic
## 1 Introduction
Hence, the IoT-based smart city network that operates in a highly dynamic environment with diverse service providers imposes several challenges to optimize data forwarding approach while preserving network resources. The context-awareness features, for instance, residual energy level, resource utilization, link quality, etc. are introduced into the proposed context-oriented objective function (COOF) for optimizing the RPL route selection mechanism to overcome the above challenges. Additionally, in RPL specification, both node and/or link metrics are used to construct the DAGs [9], and these metrics are used in OF to satisfy the different performance objectives for the LLNs. Therefore, the OF can be used to discover and maintain routing paths according to the application requirements. Two OFs have been standardized in RPL standard to optimize the path selection towards the root node. The first one is objective function zero (OF0), as a routing metric, it uses hop count [10], and the second one is the minimum rank with hysteresis objective function (MRHOF), and as a routing metric, it uses expected transmission count (ETX) [11]. However, both the OFs are primarily designed for low data traffic networks with low dynamic traffic. Therefore, under heavy and dynamic traffic scenarios, it may encounter serious problems. Further, both OFs merely rely on a single metric, which performs poorly in LLN under heavy and dynamic traffic [12]. Besides, the possibility of merging multiple routing metrics to set different goals for heterogeneous networks is not well addressed. Another limitation of the RPL specification is metric configuration. No specific mechanism for combining multiple routing metrics is defined. When considering all of these facts, in this paper, we propose an improved RPL while considering a new context-oriented objective function. The new COOF utilizes knowledge regarding the network resources to select the optimum parent towards the root by combining multiple metrics. COOF is aware of the context through its ability to gather contextual information regarding the condition of a given link and node in the network. The following are the main contribution of this paper:  
* This paper suggests improvements to RPL for IoT based smart city network with high- speed sensing data flows. For this, we suggest a new context-oriented objective function that recursively examines the last state of a node on the path to the root. More precisely, a single routing metric problem can be solved while using fuzzy logic techniques that simultaneously use multiple routing metrics. Fuzzy-based route selection technology allows for the network to establish high-qualityroutes to meet specific application contexts. The metrics used are designed to respond to the dynamic needs of the network. * We propose a new routing metric called queue fluctuation index, which considers the queue utilization of a node. We utilize queue fluctuations that take the difference between the current queue length and the last-round queue occupancy into account. * We aim to put forward a simple conceptual context-aware system architecture for IoT based smart city applications. The hybrid architecture indicates the characteristic of the metric parameters. * We conduct extensive simulation tests to verify that COOF can adapt to network dynamicity and context changes than the default OFs. The remaining of the paper is organized, as follows. Section 2 discusses the related research work. A brief description of the RPL protocol is presented in Section 3. In Section 4, we describe our proposed approach in detail. Section 5 presents the experiment setup and evaluates the performance of the proposed work in different scenarios and compares the results. Section 6 discusses the key aspects of the proposed work and future plan. Finally, in Section 7, we conclude the paper.