VANETs have emerged as an exciting research and application area. Increasingly vehicles are being equipped with embedded sensors, processing and wireless communication capabilities. This has opened a myriad of possibilities for powerful and potential life-changing applications on safety, efficiency, comfort, public collaboration and participation, while they are on the road. Although, considered as a special case of a Mobile Ad Hoc Network, the high but constrained mobility of vehicles bring new challenges to data communication and application design in VANETs. This is due to their highly dynamic and intermittent connected topology and different application's QoS requirements. In this work, we survey VANETs focusing on their communication and application challenges. In particular, we discuss the protocol stack of this type of network, and provide a qualitative comparison between most common protocols in the literature. We then present a detailed discussion of different categories of VANET applications. Finally, we discuss open research problems to encourage the design of new VANET solutions.

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Abstract. The key challenge in the design of wireless sensor networks is maximizing their lifetime. The information about the amount of available energy in each part of the network is called the energy map and can be useful to increase the lifetime of the network. In this paper, we address the problem of constructing the energy map of a wireless sensor network using prediction-based approaches. We also present an energy dissipation model that is used to simulate the behavior of a sensor node in terms of energy consumption. Simulation results compare the performance of the prediction-based approaches with a naive one in which no prediction is used. The results show that the prediction-based approaches outperform the naive in a variety of parameters.

A fundamental issue in the design of a wireless sensor network is to devise mechanisms to make efficient use of its energy, and thus, extend its lifetime. The information about the amount of available energy in each part of the network is called the energy map and can be useful to increase the lifetime of the network. In this paper, we address the problem of constructing the energy map of a wireless sensor network using prediction-based approach. Simulation results compare the performance of a prediction-based approach with a naive one in which no prediction is used. Results show that the prediction-based approach outperforms the naive in a variety of parameters. We also investigate the possibility of sampling the energy information in some nodes in the network in order to diminish the number of energy information packets. Results show that the use of sampling techniques produce more constant error curves.