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Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of Things (IoT) devices to support various types of real-time IoT applications. However, due to the mobility of users and a wide range of IoT…
With the advent of ever-growing vehicular applications, vehicular edge computing (VEC) has been a promising solution to augment the computing capacity of future smart vehicles. The ultimate challenge to fulfill the quality of service (QoS)…
Accurate latency computation is essential for the Internet of Things (IoT) since the connected devices generate a vast amount of data that is processed on cloud infrastructure. However, the cloud is not an optimal solution. To overcome this…
To leverage the vast amounts of onboard data while ensuring privacy and security, federated learning (FL) is emerging as a promising technology for supporting a wide range of vehicular applications. Although FL has great potential to…
Routing of messages in Vehicular Ad-hoc Networks (VANETs) is challenging due to obstacle shadowing regions with high vehicle densities, which leads to frequent disconnection problems and blocks radio wave propagation between vehicles.…
The emergence of the Fog computing paradigm that leverages in-network virtualized resources raises important challenges in terms of resource and IoT application management in a heterogeneous environment offering only limited computing…
Vehicle platooning facilitates the partial automation of vehicles and can significantly reduce fuel consumption. Mobile communication infrastructure makes it possible to dynamically coordinate the formation of platoons en route. We consider…
Despite the significant advances in vehicle automation and electrification, the next-decade aspirations for massive deployments of autonomous electric mobility on demand (AEMoD) services are still threatened by two major bottlenecks, namely…
Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more…
The emerging vehicular connected applications, such as cooperative automated driving and intersection collision warning, show great potentials to improve the driving safety, where vehicles can share the data collected by a variety of…
The Software-Defined Air-Ground integrated Vehicular (SD-AGV) networks have emerged as a promising paradigm, which realize the flexible on-ground resource sharing to support innovative applications for UAVs with heavy computational…
Automotive services for connected vehicles are one of the main fields of application for new-generation mobile networks as well as for the edge computing paradigm. In this paper, we investigate a system architecture that integrates the…
Fog computing reduces the latency induced by distant clouds by enabling the deployment of some application components at the edge of the network, on fog nodes, while keeping others in the cloud. Application components can be implemented as…
Multi-access edge computing (MEC) is a promising solution for providing the computational resources and low latency required by vehicular services such as autonomous driving. It enables cars to offload computationally intensive tasks to…
In the context of evolving smart cities and autonomous transportation systems, Vehicular Ad-hoc Networks (VANETs) and the Internet of Vehicles (IoV) are growing in significance. Vehicles are becoming more than just a means of…
With the rapid development of vehicular networks, various applications that require high computation resources have emerged. To efficiently execute these applications, vehicular edge computing (VEC) can be employed. VEC offloads the…
The transformation of smart mobility is unprecedented--Autonomous, shared and electric connected vehicles, along with the urgent need to meet ambitious net-zero targets by shifting to low-carbon transport modalities result in new traffic…
Despite the significant advances in vehicle automation and electrification, the next-decade aspirations for massive deployments of autonomous electric mobility on demand (AEMoD) services are still threatened by two major bottlenecks, namely…
Recently, to deliver services directly to the network edge, fog computing, an emerging and developing technology, acts as a layer between the cloud and the IoT worlds. The cloud or fog computing nodes could be selected by IoTs applications…
The increasing demand for rich multimedia services and the emergence of the Internet-of-Things (IoT) pose challenging requirements for the next generation vehicular networks. Such challenges are largely related to high spectral efficiency…