Probabilistic flooding is commonly considered in vehicular ad-hoc networks (VANETs) to alleviate the celebrated broadcast storm problem. Heuristics and simulations have so far proved to be an efficient way with which to design probabilistic information dissemination solutions with demonstrated effectiveness. Supplementing with mathematical analysis for both design and evaluation is expected to generalize the results, and increase the confidence in the proposed solutions. So far, this has been limited due to the difficulties associated with the underlying stochastic dependencies. In this paper, we introduce simple models of single and multiple lane roads to design effective probabilistic flooding schemes for VANETs. The proposed analytical framework offers a novel and generic tool which can cover any number of lanes, vehicle transmission range, and density. We derive difference equations whose solutions yield the probability of all vehicles receiving the emergency warning message as a function of the rebroadcast probability, the number of neighbors of each vehicle, and the dissemination distance. The models are validated using simulations, realistically representing both the traffic and networking aspects, and are used as a baseline to design two schemes for information dissemination which employ probabilistic flooding. The one attempts direct calculation of the required parameters whereas the other adaptively regulates the rebroadcast probability based on the vehicle speed. The schemes are evaluated using simulations and are found to achieve significant performance improvements compared to blind flooding with respect to the achieved reachability, end-to-end delay, and number of rebroadcasts, comparable to the performance achieved by optimal flooding, obtained via brute force.

A number of probabilistic flooding schemes have been recently considered in VANETs to address problems of information dissemination in safety applications. The design approach has so far been simulative, a method which does not guarantee that the derived protocols will work when the simulation settings are violated in practice. In this paper, motivated by the need to design information dissemination protocols with verifiable properties prior to implementation, we employ mathematical models of single and multiple lane roads to investigate probabilistic flooding in VANETs using mathematical analysis. We demonstrate that the system can be described by linear difference equations the solutions of which yield the probability of all vehicles receiving the critical message as a function of the rebroadcast probability, the number of neighbors of each vehicle and the number of vehicles. We utilize the obtained solutions to derive the desired rebroadcast probabilities as a function of the transmission range, the vehicle density and the dissemination distance. The obtained results are in line with results obtained using extensive simulations and can be used as a baseline to develop information dissemination protocols with verifiable properties.

The high popularity of Wi-Fi technology for wireless access has led to a common problem of densely deployed access points (APs) in residential or commercial buildings, competing to use the same or overlapping frequency channels and causing a degradation to the user experience due to excessive interference. This degradation is partly caused by the restriction where each client device is allowed to be served only by one of a very limited set of APs (e.g. belonging to the same residential unit), even if it is within range of (or even has a better signal quality to) many other APs. In this paper, we propose a cooperative strategy to mitigate the interference and enhance the quality of service in dense wireless deployments, by having neighboring APs agree to take turns (e.g. in round-robin fashion) to serve each other's clients. We present and analyze a cooperative game-theoretic model of the incentives involved in such cooperation and identify the conditions under which cooperation would be beneficial for the participating APs.

Human error is one of the principal influencing factors that lead to road accidents, and is attributed to increased mental workload induced by distractions such as advertisements and in-vehicle music. Workload, however, is characterized by intrinsic properties and hence difficult to be observed and quantified. Phenotype behaviours, such as lateral deviations, speed and headway, act as good indicators of driver workload and driving style. Driving simulators emerged as a promising technology for the analysis of driving conditions and road users' behaviour in an attempt to tackle the problem of road accidents. However, the cost of designing or owning a simulator to conduct a safety analysis is prohibitive for many government agencies. The work presented herein demonstrates the design and development of a driving simulator, using a 3D game engine. The simulator was employed to analyze the driving behaviours of local road users for a chosen black spot in Nicosia-Cyprus. Data collected from the experiments were analyzed and preliminary results are presented along with conclusions.