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Data Offloading in 5G-Enabled Software-Defined Vehicular Networks: A Stackelberg-Game-Based Approach
Thapar University, Patiala, India.
Thapar University, Patiala, India.
Thapar University, Patiala, India.
National Institute of Telecommunications (Inatel), Santa Rita do Sapucaí, Brazil; University of Beira Interior, Covilhã, Portugal; ITMO University, St. Petersburg, Russia; University of Fortaleza (Unifor), Fortaleza, Brazil.
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2017 (English)In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 55, no 8, 100-108 p.Article in journal (Refereed) Published
Abstract [en]

Data offloading using vehicles is one of the most challenging tasks to perform due to the high mobility of vehicles. There are many solutions available for this purpose, but due to the inefficient management of data along with the control decisions, these solutions are not adequate to provide data offloading by making use of the available networks. Moreover, with the advent of 5G and related technologies, there is a need to cope with high speed and traffic congestion in the existing infrastructure used for data offloading. Hence, to make intelligent decisions for data offloading, an SDN-based scheme is presented in this article. In the proposed scheme, an SDNbased controller is designed that makes decisions for data offloading by using the priority manager and load balancer. Using these two managers in SDN-based controllers, traffic routing is managed efficiently even with an increase in the size of the network. Moreover, a single-leader multi-follower Stackelberg game for network selection is also used for data offloading. The proposed scheme is evaluated with respect to several parameters where its performance was found to be superior in comparison to the existing schemes. © Copyright 2017 IEEE

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2017. Vol. 55, no 8, 100-108 p.
National Category
Communication Systems Telecommunications
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URN: urn:nbn:se:hh:diva-34696DOI: 10.1109/MCOM.2017.1601224OAI: oai:DiVA.org:hh-34696DiVA: diva2:1130430
Available from: 2017-08-09 Created: 2017-08-09 Last updated: 2017-08-10Bibliographically approved

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