Currently, the coexistence of multiple users and devices challenges the network's ability to reliably connect them. This article proposes a novel communication architecture that satisfies the requirements of fifth-generation (5G) mobile network applications. In particular, this architecture extends and combines ultra-dense networking (UDN), multi-access edge computing (MEC), and virtual infrastructure

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption

Proper scheduling of downlink (RSU-to-vehicle) communication reduces power consumption of Road Side Unit (RSU) in green vehicular networks. In highway scenarios, due to high deployment cost of RSUs, it is necessary to leave some areas uncovered in which vehicles cannot get direct access to the RSUs. Therefore, a vehicle with large data requirement may enter into an uncovered area without completely

The rapid adoption of technology for the purpose of connecting all things to a global network can be witnessed in those ranging from simple applications, such as toasters, to more complex ones, such as vehicles. In particular, the connected vehicles which have emerged from this adoption utilize various sensors and external connections to either better allow its user to make a more informed decision

Since the inception of smart cities, vehicular networks has introduced new dimensions for delay-sensitive applications. The use of backend cloud data centers is no longer a viable solution due to incurred latency. Thus, to support such applications, computing devices are placed at edge locations to reduce communication delay improving the quality of service. However, in a congested environment, these

Participatory Sensing (PS) is a known paradigm of collaborative networks which provides incentives for users to participate in sensing tasks of Regions of Interest (RoIs). A challenge in wireless networking, however, is to balance the amount of data collected by users without imposing excessive load to the network. In this direction, this paper proposes a centralized system to adapt the sampling rate