ODCRep: Origin-Destination-Based Content Replication for Vehicular Networks

The evolution of vehicular network applications, from simple alert message exchange to more elaborate and sophisticated systems, boosts the need for content delivery solutions. A useful technique, in this case, is content replication, in which strategically selected vehicles replicate content and he...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2015-12, Vol.64 (12), p.5563-5574
Main Authors: Silva, Fabricio A., Boukerche, Azzedine, Braga Silva, Thais R. M., Benevenuto, Fabricio, Ruiz, Linnyer B., Loureiro, Antonio A. F.
Format: Article
Language:English
Subjects:
Algorithms
Connected vehicles
Consumption
content availability
content delivery
Content distribution networks
content replication
Density
Dynamical systems
Dynamics
Mathematical models
Network topology
Networks
replica allocation
Replication
Vehicle dynamics
Vehicular ad hoc networks
Vehicular networks
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Summary:The evolution of vehicular network applications, from simple alert message exchange to more elaborate and sophisticated systems, boosts the need for content delivery solutions. A useful technique, in this case, is content replication, in which strategically selected vehicles replicate content and help in the delivery process. However, content replication is particularly challenging in vehicular networks, due to their special characteristics, such as highly dynamic topology, diverse density, and large-scale scenarios. Although there has been progress in routing and dissemination solutions for vehicular networks, few studies have concentrated on the content replication problem. To address this issue, we propose an origin-destination-based content replication (ODCRep) solution that focuses on balancing the number of replicas across the application area. Differently from existing solutions, ODCRep relies only on the origin-destination information and uses computationally efficient algorithms. Results from exhaustive simulations show that ODCRep can achieve high coverage, yet can also consume fewer resources than existing solutions.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2015.2487679