6,736 research outputs found
Faster Information Propagation on Highways: a Virtual MIMO Approach
In vehicular communications, traffic-related information should be spread
over the network as quickly as possible to maintain a safe and reliable
transportation system. This motivates us to develop more efficient information
propagation schemes. In this paper, we propose a novel cluster-based
cooperative information forwarding scheme, in which the vehicles
opportunistically form virtual antenna arrays to boost one-hop transmission
range and therefore accelerate information propagation along the highway. Both
closed-form results of the transmission range gain and the improved Information
Propagation Speed (IPS) are derived and verified by simulations. It is observed
that the proposed scheme demonstrates the most significant IPS gain in moderate
traffic scenarios, whereas too dense or too sparse vehicle density results in
less gain. Moreover, it is also shown that increased mobility offers more
contact opportunities and thus facilitates information propagation.Comment: IEEE 2014 Global Telecommunications Conference (GLOBECOM 2014) -
Communication Theory Symposiu
SDDV: scalable data dissemination in vehicular ad hoc networks
An important challenge in the domain of vehicular ad hoc networks (VANET) is the scalability of data dissemination. Under dense traffic conditions, the large number of communicating vehicles can easily result in a congested wireless channel. In that situation, delays and packet losses increase to a level where the VANET cannot be applied for road safety applications anymore. This paper introduces scalable data dissemination in vehicular ad hoc networks (SDDV), a holistic solution to this problem. It is composed of several techniques spread across the different layers of the protocol stack. Simulation results are presented that illustrate the severity of the scalability problem when applying common state-of-the-art techniques and parameters. Starting from such a baseline solution, optimization techniques are gradually added to SDDV until the scalability problem is entirely solved. Besides the performance evaluation based on simulations, the paper ends with an evaluation of the final SDDV configuration on real hardware. Experiments including 110 nodes are performed on the iMinds w-iLab.t wireless lab. The results of these experiments confirm the results obtained in the corresponding simulations
On the Experimental Evaluation of Vehicular Networks: Issues, Requirements and Methodology Applied to a Real Use Case
One of the most challenging fields in vehicular communications has been the
experimental assessment of protocols and novel technologies. Researchers
usually tend to simulate vehicular scenarios and/or partially validate new
contributions in the area by using constrained testbeds and carrying out minor
tests. In this line, the present work reviews the issues that pioneers in the
area of vehicular communications and, in general, in telematics, have to deal
with if they want to perform a good evaluation campaign by real testing. The
key needs for a good experimental evaluation is the use of proper software
tools for gathering testing data, post-processing and generating relevant
figures of merit and, finally, properly showing the most important results. For
this reason, a key contribution of this paper is the presentation of an
evaluation environment called AnaVANET, which covers the previous needs. By
using this tool and presenting a reference case of study, a generic testing
methodology is described and applied. This way, the usage of the IPv6 protocol
over a vehicle-to-vehicle routing protocol, and supporting IETF-based network
mobility, is tested at the same time the main features of the AnaVANET system
are presented. This work contributes in laying the foundations for a proper
experimental evaluation of vehicular networks and will be useful for many
researchers in the area.Comment: in EAI Endorsed Transactions on Industrial Networks and Intelligent
Systems, 201
Stuck in Traffic (SiT) Attacks: A Framework for Identifying Stealthy Attacks that Cause Traffic Congestion
Recent advances in wireless technologies have enabled many new applications
in Intelligent Transportation Systems (ITS) such as collision avoidance,
cooperative driving, congestion avoidance, and traffic optimization. Due to the
vulnerable nature of wireless communication against interference and
intentional jamming, ITS face new challenges to ensure the reliability and the
safety of the overall system. In this paper, we expose a class of stealthy
attacks -- Stuck in Traffic (SiT) attacks -- that aim to cause congestion by
exploiting how drivers make decisions based on smart traffic signs. An attacker
mounting a SiT attack solves a Markov Decision Process problem to find
optimal/suboptimal attack policies in which he/she interferes with a
well-chosen subset of signals that are based on the state of the system. We
apply Approximate Policy Iteration (API) algorithms to derive potent attack
policies. We evaluate their performance on a number of systems and compare them
to other attack policies including random, myopic and DoS attack policies. The
generated policies, albeit suboptimal, are shown to significantly outperform
other attack policies as they maximize the expected cumulative reward from the
standpoint of the attacker
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