5,389 research outputs found
A content dissemination framework for vehicular networking
Vehicular Networks are a peculiar class of wireless mobile networks in which vehicles are equipped with radio interfaces and are, therefore, able to communicate with fixed infrastructure (if available) or other vehicles.
Content dissemination has a potential number of applications in vehicular networking,
including advertising, traffic warnings, parking
notifications and emergency
announcements. This thesis addresses two possible dissemination strategies: i) Push-based that is aiming to proactively deliver information to a group of vehicles based on
their interests and the level of matching content, and ii) Pull-based that is allowing
vehicles to explicitly request custom information.
Our dissemination framework is taking into consideration very specific information
only available in vehicular networks: the geographical data produced by the navigation
system. With its aid, a vehicle's mobility patterns become predictable. This information
is exploited to efficiently deliver the content where it is needed. Furthermore, we use
the navigation system to automatically filter information which might be relevant to
the vehicles.
Our framework has been designed and implemented in .NET C# and Microsoft
MapPoint. It was tested using a small number of vehicles in the area of Cambridge,
UK. Moreover, to prove the correctness of our protocols, we further evaluated it in a
large-scale network simulation over a number of realistic vehicular trace-based scenarios.
Finally, we built a test-case application aiming to prove that vehicles can gain
from such a framework. In this application every vehicle collects and disseminates road
traffic information. Vehicles that receive this information can individually evaluate the
traffic conditions and take an alternative route, if needed. To evaluate this approach,
we collaborated with UCLA's Network Research Lab (NRL), to build a simulator that
combines network and dynamic mobility emulation simultaneously. When our dissemination
framework is used, the drivers can considerably reduce their trip-times
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
Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles
Vehicular Ad-hoc Networks (VANET) enable efficient communication between
vehicles with the aim of improving road safety. However, the growing number of
vehicles in dense regions and obstacle shadowing regions like Manhattan and
other downtown areas leads to frequent disconnection problems resulting in
disrupted radio wave propagation between vehicles. To address this issue and to
transmit critical messages between vehicles and drones deployed from service
vehicles to overcome road incidents and obstacles, we proposed a hybrid
technique based on fog computing called Hybrid-Vehfog to disseminate messages
in obstacle shadowing regions, and multi-hop technique to disseminate messages
in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to
changes in an environment and benefits in efficiency with robust drone
deployment capability as needed. Performance of Hybrid-Vehfog is carried out in
Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators.
The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message
Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP),
PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data
Networking (NDN) with mobility, and flooding schemes at all vehicle densities
and simulation times
Social-aware Forwarding in Opportunistic Wireless Networks: Content Awareness or Obliviousness?
With the current host-based Internet architecture, networking faces
limitations in dynamic scenarios, due mostly to host mobility. The ICN paradigm
mitigates such problems by releasing the need to have an end-to-end transport
session established during the life time of the data transfer. Moreover, the
ICN concept solves the mismatch between the Internet architecture and the way
users would like to use it: currently a user needs to know the topological
location of the hosts involved in the communication when he/she just wants to
get the data, independently of its location. Most of the research efforts aim
to come up with a stable ICN architecture in fixed networks, with few examples
in ad-hoc and vehicular networks. However, the Internet is becoming more
pervasive with powerful personal mobile devices that allow users to form
dynamic networks in which content may be exchanged at all times and with low
cost. Such pervasive wireless networks suffer with different levels of
disruption given user mobility, physical obstacles, lack of cooperation,
intermittent connectivity, among others. This paper discusses the combination
of content knowledge (e.g., type and interested parties) and social awareness
within opportunistic networking as to drive the deployment of ICN solutions in
disruptive networking scenarios. With this goal in mind, we go over few
examples of social-aware content-based opportunistic networking proposals that
consider social awareness to allow content dissemination independently of the
level of network disruption. To show how much content knowledge can improve
social-based solutions, we illustrate by means of simulation some
content-oblivious/oriented proposals in scenarios based on synthetic mobility
patterns and real human traces.Comment: 7 pages, 6 figure
On the Potential of Generic Modeling for VANET Data Aggregation Protocols
In-network data aggregation is a promising communication mechanism to reduce bandwidth requirements of applications in vehicular ad-hoc networks (VANETs). Many aggregation schemes have been proposed, often with varying features. Most aggregation schemes are tailored to specific application scenarios and for specific aggregation operations. Comparative evaluation of different aggregation schemes is therefore difficult. An application centric view of aggregation does also not tap into the potential of cross application aggregation. Generic modeling may help to unlock this potential. We outline a generic modeling approach to enable improved comparability of aggregation schemes and facilitate joint optimization for different applications of aggregation schemes for VANETs. This work outlines the requirements and general concept of a generic modeling approach and identifies open challenges
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