746 research outputs found
Fair sharing of bandwidth in VANETs
We address the challenge of how to share the limited wireless
channel capacity for the exchange of safety-related information
in a fully deployed vehicular ad hoc network (VANET). In
particular, we study the situation that arises when the number
of nodes sending periodic safety messages is too high in a
specific area. In order to achieve a good performance of
safety-related protocols, we propose to limit the load sent to
the channel using a strict fairness criterion among the nodes. A
formal definition of this problem is presented in terms of a
max-min optimization problem with an extra condition of per-node
maximality. Furthermore, we propose FPAV, a power control
algorithm which finds the optimum transmission range of every
node, and formally prove its validity under idealistic
conditions. Simulations are performed to visualize the result of
FPAV in a couple of road situations. Finally, we discuss the
issues that must be taken into account when implementing FPAV
A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks
One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has
attracted the researchers' consideration is congestion control. Accordingly,
many algorithms have been proposed to alleviate the congestion problem,
although it is hard to find an appropriate algorithm for applications and
safety messages among them. Safety messages encompass beacons and event-driven
messages. Delay and reliability are essential requirements for event-driven
messages. In crowded networks where beacon messages are broadcasted at a high
number of frequencies by many vehicles, the Control Channel (CCH), which used
for beacons sending, will be easily congested. On the other hand, to guarantee
the reliability and timely delivery of event-driven messages, having a
congestion free control channel is a necessity. Thus, consideration of this
study is given to find a solution for the congestion problem in VANETs by
taking a comprehensive look at the existent congestion control algorithms. In
addition, the taxonomy for congestion control algorithms in VANETs is presented
based on three classes, namely, proactive, reactive and hybrid. Finally, we
have found the criteria in which fulfill prerequisite of a good congestion
control algorithm
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MobileTrust: Secure Knowledge Integration in VANETs
Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy
Cognitive radio-enabled Internet of Vehicles (IoVs): a cooperative spectrum sensing and allocation for vehicular communication
Internet of Things (IoTs) era is expected to empower all aspects of Intelligent Transportation System (ITS) to improve transport safety and reduce road accidents. US Federal Communication Commission (FCC) officially allocated 75MHz spectrum in the 5.9GHz band to support vehicular communication which many studies have found insufficient. In this paper, we studied the application of Cognitive Radio (CR) technology to IoVs in order to increase the spectrum resource opportunities available for vehicular communication, especially when the officially allocated 75MHz spectrum in 5.9GHz band is not enough due to high demands as a result of increasing number of connected vehicles as already foreseen in the near era of IoTs. We proposed a novel CR Assisted Vehicular NETwork (CRAVNET) framework which empowers CR enabled vehicles to make opportunistic usage of licensed spectrum bands on the highways. We also developed a novel co-operative three-state spectrum sensing and allocation model which makes CR vehicular secondary units (SUs) aware of additional spectrum resources opportunities on their current and future positions and applies optimal sensing node allocation algorithm to guarantee timely acquisition of the available channels within a limited sensing time. The results of the theoretical analyses and simulation experiments have demonstrated that the proposed model can significantly improve the performance of a cooperative spectrum sensing and provide vehicles with additional spectrum opportunities without harmful interference against the Primary Users (PUs) activities
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