Connected vehicles promise to enable a wide range of new automotive services that will improve road safety, ease traffic management, and make the overall travel experience more enjoyable. However, they also open significant new surfaces for attacks on the electronics that control most of modern vehicle operations. In particular, the emergence of vehicle-to-vehicle (V2V) communication risks to lay fertile ground for self-propagating mobile malware that targets automobile environments. In this work, we perform a first study on the dynamics of vehicular malware epidemics in a large-scale road network, and unveil how a reasonably fast worm can easily infect thousands of vehicles in minutes. We determine how such dynamics are affected by a number of parameters, including the diffusion of the vulnerability, the penetration ratio and range of the V2V communication technology, or the worm self-propagation mechanism. We also propose a simple yet very effective numerical model of the worm spreading process, and prove it to be able to mimic the results of computationally expensive network simulations. Finally, we leverage the model to characterize the dangerousness of the geographical location where the worm is first injected, as well as for efficient containment of the epidemics through the cellular network.

There is a growing need for vehicular mobility datasets that can be employed in the simulative evaluation of protocols and architectures designed for upcoming vehicular networks. Such datasets should be realistic, publicly available, and heterogeneous, i.e., they should capture varied traffic conditions. In this paper, we contribute to the ongoing effort to define such mobility scenarios by introducing a novel set of traces for vehicular network simulation. Our traces are derived from high-resolution real-world traffic counts, and describe the road traffic on two highways around Madrid, Spain, at several hours of different working days. We provide a thorough discussion of the real-world data underlying our study, and of the synthetic trace generation process. Finally, we assess the potential impact of our dataset on networking studies, by characterizing the connectivity of vehicular networks built on the different traces. Our results underscore the dramatic impact that relatively small communication range variations have on the network. Also, they unveil previously unknown temporal dynamics of the topology of highway vehicular networks, and identify their causes.

The surge in vehicular network research has led, over the last few years, to the proposal of countless network solutions specifically designed for vehicular environments. A vast majority of such solutions has been evaluated by means of simulation, since experimental and analytical approaches are often impractical and intractable, respectively. The reliability of the simulative evaluation is thus paramount to the performance analysis of vehicular networks, and the first distinctive feature that has to be properly accounted for is the mobility of vehicles, i.e., network nodes. Notwithstanding the improvements that vehicular mobility modeling has undergone over the last decade, no vehicular mobility dataset is publicly available today that captures both the macroscopic and microscopic dynamics of road traffic over a large urban region. In this paper, we present a realistic synthetic dataset, covering 24 hours of car traffic in a 400-km2region around the city of Köln, in Germany. We describe the generation process and outline how the dataset improves the traces currently employed for the simulative evaluation of vehicular networks. We also show the potential impact that such a comprehensive mobility dataset has on the network protocol performance analysis, demonstrating how incomplete representations of vehicular mobility may result in over-optimistic network connectivity and protocol performance.

The large-scale adoption of vehicle-to-vehicle (V2V) communication technologies risks to significantly widen the attack surface available to mobile malware targeting critical automobile operations. Given that outbreaks of vehicular computer worms self-propagating through V2V links could pose a significant threat to road traffic safety, it is important to understand the dynamics of such epidemics and to prepare adequate countermeasures. In this paper we perform a comprehensive characterization of the infection process of variously behaving vehicular worms on a road traffic scenario of unprecedented scale and heterogeneity. We then propose a simple yet effective data-driven model of the worm epidemics, and we show how it can be leveraged for smart patching infected vehicles through the cellular network in presence of a vehicular worm outbreak.

We consider a complex (i.e., nonlinear) road scenario where users aboard vehicles equipped with communication interfaces are interested in downloading large files from road-side Access Points (APs). We investigate the possibility of exploiting opportunistic encounters among mobile nodes so to augment the transfer rate experienced by vehicular downloaders. To that end, we devise solutions for the selection of carriers and data chunks at the APs, and evaluate them in real-world road topologies, under different AP deployment strategies. Through extensive simulations, we show that carry&forward transfers can significantly increase the download rate of vehicular users in urban/suburban environments, and that such a result holds throughout diverse mobility scenarios, AP placements and network loads.

Wireless nodes such as smart-phones in which the WiFi wireless card is continuously on, consume battery energy in just a few hours. Moreover, in many scenarios, an always-on wireless card is useless because there is often no need for transmission and/or reception. This fact is exacerbated in Delay/Disruptive Tolerant Network (DTN) environments, in which nodes exchange Delay Tolerant Objects (DTO) when they meet. Power Saving Management (PSM) techniques enable the lifetime of the nodes to be extended. This paper analyses the trade-offs that appear when wireless nodes periodically turn off the wireless card in order to save battery in DTN environments. The paper shows the conditions in which a node can switch off the battery without impacting the peer-to-peer contact probability, and those in which this contact probability is decreased. For example, it is shown that node lifetime can be doubled while keeping the peer-to-peer contact probability equal to one. But, further increase of the node lifetime quickly decreases peer-to-peer contact probability. Finally, the impact of power savings in DTO dissemination time is also analyzed.

Vehicular Ad Hoc Networks are networks characterized by intermittent connectivity and rapid changes in their topology. This paper addresses car-to-road communications in which vehicles use Access Points (AP) in a Delay Tolerant Network architecture. Results show how the combination of a Delay-Cooperative ARQ mechanism reduces packet losses and in conjunction with a Carry-and-Forward cooperative mechanism improves performance parameters in terms of total file transfer delay and number of AP needed to download files.

We consider that a given number of dissemination points (DPs) have to be deployed for disseminating information to vehicles travelling in an urban area. We formulate our problem as a maximum coverage problem (MCP) so as to maximize the number of vehicles that get in contact with the DPs and as a second step with a sufficient amount of time. Since the MCP is NP-hard, we solve it though heuristic algorithms. Evaluation of the proposed solutions in a realistic urban environment shows how knowledge of vehicular mobility plays a major role in achieving an optimal coverage of mobile users, and that simple heuristics provide near-optimal results even in large-scale scenarios.