Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

In recent years, the network technology known as Internet of Vehicles (IoV) has been developed to improve road safety and vehicle security, with the goal of servicing the digital demands of car drivers and passengers. However, the highly dynamical network topology that characterizes these networks, and which often leads to discontinuous transmissions, is one of the most significant challenges of IoV. To address this issue, IoV infrastructure-based components known as roadside units (RSU) are designed to play a critical role by providing continuous transmission coverage and permanent connectivity. However, the main challenges that arise when deploying RSUs are balancing IoVs’ performances and total cost so that optimal vehicle service coverage is provided with respect to some target Quality of Service (QoS) such as: service coverage, throughput, low latency, or energy consumption. This paper provides an in-depth survey of RSU deployment in IoV networks, discussing recent research trends in this field, and summarizing of a number of previous papers on the subject. Furthermore, we highlight that two classes of RSU deployment can be found in the literature—static and dynamic—the latter being based on vehicle mobility. A comparison between the existing RSU deployment schemes proposed in existing literature, as well as the various networking metrics, are presented and discussed. Our comparative study confirms that the performance of the different RSU placement solutions heavily depends on several factors such as road shape, particularity of road segments (like accident-prone ones), wireless access methods, mobility model, and vehicles’ distribution over time and space. Besides that, we review the most important RSU placement approaches, highlighting their strengths and limitations. Finally, this survey concludes by presenting some future research directions in this domain.

The Internet of Vehicles (IoV) connects vehicles together and also to other internet of things components such as sensors and smart devices. The huge amount of data generated by these components is stored in the cloud, so does the services offered which are not limited to safety applications but also to infotainment where most of these services use the position and identity of the vehicle. Due to these requirements, the privacy of road users is at threat. Thus, preserving it is highly important as it is directly related to their safety. If a specific user is targeted on the road by an attacker who knows his/her identity and real-time location, the consequences can vary from simple stalking to assassination. This paper proposes a new solution called Concerted Silence-based Location Privacy Preserving Scheme for Internet of Vehicles (CSLPPS) that ensures the anonymous and unlinkable participation in the IoV location-based services and vehicular networks safety applications. This scheme relies on the synchronization of the identifier change between the cooperative vehicles to enter a silent period simultaneously before continuing their cyber-activity with new identifiers. The simulation and study of performance proved efficiency of CSLPPS against a modeled global passive attacker and when compared to state-of-art solution.