Vehicular Ad-hoc Networks (VANETs) have been recently attracting an increasing attention from both research and industry communities. One of the challenges posed by the study of VANETs is the definition of a vehicular mobility model providing an accurate and realistic vehicular mobility description at both macroscopic and microscopic levels. Another challenge is to be able to dynamically alter this vehicular mobility as a consequence of the vehicular communication protocols. Many mobility models have been developed by the community in order to solve these two issues. However, due to the large number of available models claiming to be adapted to vehicular traffic, and also due to their different and somehow incomparable features, understanding their true characteristics, their degree of realism with respect to vehicular mobility, and real capabilities is a hard task. In this survey, we first introduce a framework that proposes a guideline for the generation of vehicular mobility models. Then, we illustrate the different approaches chosen by the community for the development of vehicular mobility models and their interactions with network simulators. Finally, we propose an overview and taxonomy of a large range of mobility models available for vehicular ad hoc networks. The objective is to provide readers with a guideline to easily understand and objectively compare the different models, and eventually identify the one required for their needs.

During the last few years, continuous progresses in wireless communications have opened new research fields in computer networking, aimed at extending data networks connectivity to environments where wired solutions are impracticable. Among these, vehicular traffic is attracting a growing attention from both academia and industry, due to the amount and importance of the related applications, ranging from road safety to traffic control, up to mobile entertainment. Vehicular ad-hoc networks (VANETs) are self-organized networks built up from moving vehicles, and are part of the broader class of mobile ad-hoc networks (MANETs). Because of their peculiar characteristics, VANETs require the definition of specific networking techniques, whose feasibility and performance are usually tested by means of simulation. One of the main challenges posed by VANETs simulations is the faithful characterization of vehicular mobility at both macroscopic and microscopic levels, leading to realistic non-uniform distributions of cars and velocity, and unique connectivity dynamics. In this paper, we first present and describe VanetMobiSim, a freely available generator of realistic vehicular movement traces for networks simulators. Then, VanetMobiSim is validated by illustrating how the interaction between featured macro- and micro-mobility is able to reproduce typical phenomena of vehicular traffic

Position-based routing has proven to be well suited for highly dynamic environment such as Vehicular Ad Hoc Networks (VANET) due to its simplicity. Greedy Perimeter Stateless Routing (GPSR) and Greedy Perimeter Coordinator Routing (GPCR) both use greedy algorithms to forward packets by selecting relays with the best progress towards the destination or use a recovery mode in case such solutions fail. These protocols could forward packets efficiently given that the underlying network is fully connected. However, the dynamic nature of vehicular network, such as vehicle density, traffic pattern, and radio obstacles could create unconnected networks partitions. To this end, we propose GeoDTN+Nav, a hybrid geographic routing solution enhancing the standard greedy and recovery modes exploiting the vehicular mobility and on-board vehicular navigation systems to efficiently deliver packets even in partitioned networks. GeoDTN+Nav outperforms standard geographic routing protocols such as GPSR and GPCR because it is able to estimate network partitions and then improves partitions reachability by using a store-carry-forward procedure when necessary. We propose a virtual navigation interface (VNI) to provide generalized route information to optimize such forwarding procedure. We finally evaluate the benefit of our approach first analytically and then with simulations. By using delay tolerant forwarding in sparse networks, GeoDTN+Nav greatly increases the packet delivery ratio of geographic routing protocols and provides comparable routing delay to benchmark DTN algorithms.

Fog Computing is a recent computing paradigm that is extending cloud computing towards the edge of network. Due to its proximity to end-users, dense geographical distribution, open platform and support for high mobility, Fog Computing platforms can provide services with reduced latency and improved QoS. Thus it is becoming an important enabler for consumer centric Internet of Things based applications and services that require real time operations e.g. connected vehicles, smart road intersection management and smart grid. The paper discusses one such architecture for connected vehicles with Road Side Units (RSUs) and M2M gateways including the Fog Computing Platform. M2M data processing with semantics, discovery and management of connected vehicles are briefly discussed as consumer centric IoT services enabled by the distinct characteristics of Fog Computing.