## 1 Introduction
With all these entities connected through vehicles and with many others being designed for the Internet of Things (IoT), the term ad hoc was considered obsolete by many researchers as it does not comprehensively cover the wide range of technologies involved within/connecting these entities [22; 23; 24; 25]. The concept of the Internet of Vehicles (IoV) has emerged as a broader concept to better represent the new era of vehicular networks [26]. However, since IoV is somewhat equivalent with the novel VANET architectures, which are very different from traditional VANETs, in this work we consider these two concepts interchangeable. Even though the IoV will open many possibilities for a plethora of applications, there are still many challenges that are yet to be addressed [7; 10; 27; 28]. Of the utmost importance is, for example, the management of the abundant information and resources available in these networks. Even a single vehicle generates huge amounts of data and considering the fact that the number of vehicles keeps increasing, managing these networks becomes more difficult. In addition, many new applications that require more and more resources come along continually, leading to increased complexity in network management. In this work, we deal with the resource management problem for which we propose an intelligent architecture based on Fuzzy Logic (FL) and Software Defined Networking (SDN) approaches that can efficiently manage cloud-fog-edge storage, computing, and networking resources in VANETs. By using FL, the proposed approach can manage the resources in real-time while dealing with imprecision and uncertainty. The contributions of the work are summarized as follows:  
* The paper presents an integrated system, called Integrated Fuzzy-based System for Coordination and Management of Resources (IFS-CMR), which, different from existing approaches, makes a decision following a bottom-up approach in a cloud-fog-edge architecture. * IFS-CMR considers the condition of the network created between vehicles, such as the Quality of Service (QoS) in the network and the unused amount of resources, together with the application requirements, to select the best resources for a particular situation. * IFS-CMR is composed of three subsystems, namely Fuzzy-based System for Assessment of QoS (FS-AQoS), Fuzzy-based System for Assessment of Neighbor Vehicle Processing Capability (FS-ANVPC), and Fuzzy-based System for Cloud-Fog-Edge Layer Selection (FS-CFELS), each having a key role in the proposed approach. * The feasibility of the proposed architecture in coordinating and managing the available VANETs resources is demonstrated by the results of extensive simulations. The rest of this paper is organized as follows. Section 2 provides a background overview of the emerging technologies integrated within VANETs which enable the full implementation of our proposed system, as well as a short review of several research papers relevant to this work. The proposed approach and the details of its implementation are presented in Section 3. Section 4 discusses the evaluation results. The last section, Section 5, gives some concluding remarks and ideas for future work.