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-km ² region 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.

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

In this letter, we compute the exact probability that a receiver obtains N linearly independent packets among K ≥ N received packets, when the sender/s use/s random linear network coding over a Galois Field of size q. Such condition maps to the receiver's capability to decode the original information, and its mathematical characterization helps to design the coding so to guarantee the correctness of the transmission. Our formulation represents an improvement over the current upper bound for the decoding probability, and provides theoretical grounding to simulative results in the literature.

Simulation is the tool of choice for the large-scale performance evaluation of upcoming telecommunication networking paradigms that involve users aboard vehicles, such as next-generation cellular networks for vehicular access, pure vehicular ad hoc networks, and opportunistic disruption-tolerant networks. The single most distinguishing feature of vehicular networks simulation lies in the mobility of users, which is the result of the interaction of complex macroscopic and microscopic dynamics. Notwithstanding the improvements that vehicular mobility modeling has undergone during the past few years, no car traffic trace is available today that captures both macroscopic and microscopic behaviors of drivers over a large urban region, and does so with the level of detail required for networking research. In this paper, we present a realistic synthetic dataset of the car traffic over a typical 24 hours in a 400-km ² region around the city of Köln, in Germany. We outline how our mobility description improves today's existing traces and show the potential impact that a comprehensive representation of vehicular mobility can have one the evaluation of networking technologies.