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Mobility as a service is becoming a new paradigm in the direction of travel planning on the basis of the best service offered by the travelled roads. Hence, the environment in which people move will become smarter and more and more connected to grant services along the whole path. This opens new challenges related not only to the on board connectivity and wireless access technologies, but also on the reliability and efficiency of the surrounding environment. In this context, reconfigurable meta-surfaces play a crucial role, since they can be used to coat buildings, vehicles or any other suitable surfaces and let the environment become an active part of the communication system by opportunistically redirecting (i.e., reflecting, without generating new waves) signals to the target receivers. The objective of this paper is to highlight the limits of current wireless access technologies for vehicular scenarios and to discuss the potential impact of a smart environment made of reconfigurable meta-surfaces on some next generation vehicular use cases, such as cooperative driving and vulnerable road users (VRUs) detection. In addition, a preliminary model is presented to derive, in a simplified way, the performance of an IEEE 802.11p network in terms of collision probability. Even if analytical and based on simplified assumptions, this model has been validated through simulations and allows to compare the performance of the network with and without reconfigurable meta-surfaces.

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The Internet of Things (IoT) is a rapidly growing trend within many domains, such as automotive, avionics, automation, energy, and health. IoT architecture is the system of numerous elements, including sensors, protocols, actuators, cloud services, and layers. IoT architecture plays an important role to provide desired services. Nowadays, tens of IoT architectures are provided by the research community. Many challenges have been identified by the research community, including interoperability, security and privacy, reliability, energy constraints, scalability, and lack of common standards. However, to provide suitable IoT architecture, the importance and priority of requirements in different scenarios may vary, and requirement analysis should be regarded. To this end, this paper presents a systematic mapping survey to give a review of IoT architecture and provide a structured overview of research trends. Moreover, a technical taxonomy is presented for these challenges according to reviewed studies. This classification model can be used as a guideline for future works.

Fog computing is an emerging computing paradigm that extends cloud services to the edge of the network by moving computation tasks from cloud to network edges to reduce response latency in a wireless network. Fog computing inherits the principle of peerto-peer networking, decentralization, and geographical distribution from clouds. Hence, fog computing becomes an ideal platform for readily supporting vehicular applications due to its dynamic support for mobility of clientdevices and low latent heterogeneous communication capabilities. Despite many advantages, a multitude of security and privacy issues affects the platforms and renders it as a target for unknown adversaries. This has significant implication in the development of safety critical applications, such as vehicular cloud and intelligent transportation system. This paper presents, an overview of existing security and privacy vulnerabilities in fog computing, particularly in vehicular networks. Moreover, state-of-the-art security and privacy solutions for fog based vehicular networks are analyzed. In conclusion, open challenges and future research directions are discussed.

Cloud computing provides computing and storage resources over the Internet to provide services for different industries. However, delay-sensitive applications like smart health and city applications now require computation over large amounts of data transferred to centralized cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide new solutions by bringing resources closer to the user and provide low latency and energy efficiency compared to cloud services. It is important to find optimal placement of services and resources in the three-tier IoT to achieve improved cost and resource efficiency, higher QoS, and higher level of security and privacy. In this paper, we propose a cost-aware genetic-based (CAG) task scheduling algorithm for fog-cloud environments, which improves the cost efficiency in real-time applications with hard deadlines. iFogSim simulator, which is an extended version of CloudSim is used to deploy and test the performance of the proposed method in terms of latency, network congestion, and cost. The performance results show that the proposed algorithm provides better efficiency in terms of the cost and throughput compared to Round-Robin and Minimum Response Time algorithms.

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