International audienceOne of the main ideas in the area of intelligent transport systems is to use all possible information, coming from vehicles and infrastructure, in order to make the system " smarter " and avoid potentially dangerous situations – collisions, accidents, bottlenecks... However data is sometimes unreliable due to source and communication network quality, leading vehicles or even the whole system to wrong decisions. We present a generic method for detecting dangerous events on the road. To support unreliable data sources, it uses distributed data fusion. Moreover, to deal with network failures, it relies on a self-stabilizing generic distributed algorithm. Our method mixes measurements obtained from vehicle onboard sensors as well as wireless sensors placed close to the road and connected to road side units. Each vehicle computes how confident it is about a potential dangerous event using both local and remote data. To evaluate our approach, we implemented it using a specific hardware and software platform. Moreover, we instantiated a simple, yet efficient application to detect icy roads, based on temperature measurements. Thanks to both in-lab and actual on-the-road experiments, we demonstrate the possibility to deduce proper results from unreliable data and, consequently, the correctness and usefulness of our approach

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Testbeds are indispensable tool in research and development process in wireless networks technologies. They show us how our solution is going to work in real environment. In the recent years there is a growing trend in the development of testbeds aimed to be used as tool for both research and verification of the results obtained theoretically and using simulators. We are presenting experimental vehicular network testbed based on the cheap, off-the-shelf wireless sensors that are gathering environmental data, temperature, humidity and luminosity. These sensors are connected to the road-side units (RSUs) running Linux operating system and dedicated software distribution, Airplug. This complete system (wireless sensors, RSUs and Airplug software distribution) can be used for simulation, emulation and experiments in vehicular networks but also for any other type of wireless network. We are using this system for the gathering of environmental data and then re-using collected data in the different emulation and experimental scenarios. We are showing the usefulness of our wireless sensors testbed and possible scenarios of its usage in emulation and real experiments.

Abstract. Topology control in wireless sensor networks is an important issue for scalability and energy efficiency. It is often based on graph reduction performed through the use of Gabriel Graph or Relative Neighborhood Graph. This graph reduction is usually based on geometric values. In this paper we tackle the problem of possible connectivity loss in the reduced graph by applying a battery level based reduction graph. Experiments are conducted to evaluate our proposition. Results are compared with RNG reduction which takes into account only the strength of the received signal (RSSI). Results show that our algorithm maintains network connectivity longer than solutions from the literature and balances the energy consumption over nodes.