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.
Passive RFID systems used for inventory management and asset tracking typically utilize contention-based MAC protocols, such as the standard C1G2 protocol. Although the C1G2 protocol has the advantage that it is easy to implement, it suffers from unfairness and relatively low throughput when the number of tags in the network increases. This paper proposes a token-based MAC protocol called Token-MAC for passive RFID systems, which aims a) to provide a fair chance for tags in the network to access the medium without requiring synchronization of the tags, b) to increase the overall throughput, i.e., the tag rate, and c) to enable a high number of tags to be read under limited tag read time availability, which is an especially important challenge for mobile applications. We implement Token-MAC as well as C1G2 and a TDMA-based protocol using Intel WISP passive RFID tags and perform experiments. Additionally, based on our experimental results, we develop energy harvesting and communication models for tags that we then use in simulations of the three protocols. Our experimental and simulation results all show that Token-MAC can achieve a higher tag rate and better fairness than C1G2, and it can provide better performance over a longer range compared with the TDMA-based protocol. It is also shown that Token-MAC achieves much lower tag detection delay, especially for high numbers of tags. Token-MAC is, therefore, a promising solution for passive RFID systems.
Deek, L.; Garcia-Villegas, E.; Belding, E.; Lee, S.; Almeroth, K. IEEE transactions on mobile computing Vol. 13, num. 6, p. 1242-1255 DOI: 10.1109/TMC.2013.73 Data de publicació: 2014-06-01 Article en revista
The IEEE 802.11n standard defines channel bonding that allows wireless devices to operate on 40 MHz channels by doubling their bandwidth from standard 20 MHz channels. Increasing channel width increases capacity, but it comes at the cost of decreased transmission range and greater susceptibility to interference. However, with the incorporation of Multiple-Input Multiple-Output (MIMO) technology in 802.11n, devices can now exploit the increased transmission rates from wider channels with minimal sacrifice to signal quality and range. The goal of our work is to identify the network factors that influence the performance of channel bonding in 802.11n networks and make intelligent channel bonding decisions. We discover that channel width selection should consider not only a link's signal quality, but also the strength of neighboring links, their physical rates, and interferer load. We use our findings to design and implement a network detector that successfully identifies interference conditions that affect channel bonding decisions in 100% of our test cases. Our detector can form the foundation for more robust and accurate algorithms that can adapt bandwidth to variations in channel conditions. Our findings allows us to predict the impact of network conditions on performance and make channel bonding decisions that maximize throughput.
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-km2 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.
Heterogeneous wireless systems are envisaged as the integration and joint cooperative management of diverse radio access networks and technologies through which network providers can satisfy the wide variety of user/service demands in a more efficient manner by exploiting their varying characteristics and properties. To achieve this objective, a key tool is common radio resource management technique designed to jointly manage the radio resources from different radio access technologies. In this context, this work proposes and optimizes new common radio resource management techniques designed to efficiently distribute traffic among the available radio access technologies while providing adequate quality of service levels under heterogeneous traffic scenarios. The obtained results demonstrate the ability of the proposed solutions to provide high user/service satisfaction levels while adequately exploiting the overall system resources.
We provide the first rigorous analytical results for the connectivity of dynamic random geometric graphs - a model for mobile wireless networks in which vertices move in random directions in the unit torus. The model presented here follows the one described. We provide precise asymptotic results for the expected length of the connectivity and disconnectivity periods of the network. We believe that the formal tools developed in this work could be extended to be used in more concrete settings and in more realistic models, in the same manner as the development of the connectivity threshold for static random geometric graphs has affected a lot of research done on ad hoc networks.
This paper addresses the problem of radio access technology (RAT) selection in heterogeneous multi-access/multi-service scenarios. For such purpose, a Markov model is proposed to compare the performance of various RAT selection policies within these scenarios. The novelty of the approach resides in the embedded definition of the aforementioned RAT selection policies within the Markov chain. In addition, the model also considers the constraints imposed by those users with terminals that only support a subset of all the available RATs (i.e. multi-mode terminal capabilities). Furthermore, several performance metrics may be measured to evaluate the behaviour of the proposed RAT selection policies under varying offered traffic conditions. In order to illustrate the validation and suitability of the proposed model, some examples of operative radio access networks are provided, including the GSM/EDGE Radio Access Network (GERAN) and the UMTS Radio Access Network (UTRAN), as well as several service-based, load-balancing and terminal-driven RAT selection strategies. The flexibility exhibited by the presented model enables to extend these RAT selection policies to others responding to diverse criteria. The model is successfully validated by means of comparing the Markov model results with those of system-level simulations.
Lopez-Aguilera, E.; Heusse, M.; Grunenberger, Y.; Rousseau, F.; Duda, A.; Casademont, J. IEEE transactions on mobile computing Vol. 7, num. 10, p. 1213-1227 Data de publicació: 2008-10 Article en revista