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Revenue-driven video delivery in vehicular networks with optimal resource scheduling

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dc.contributor.author Al-Hilo, Ahmed
dc.contributor.author Ebrahimi, Dariush
dc.contributor.author Sharafeddine, Sanaa
dc.contributor.author Assi, Chadi
dc.date.accessioned 2020-02-04T12:22:47Z
dc.date.available 2020-02-04T12:22:47Z
dc.date.copyright 2020 en_US
dc.identifier.issn 2214-2096 en_US
dc.identifier.uri http://hdl.handle.net/10725/11796
dc.description.abstract Vehicular network is the enabler of various services for transportation means including safety and infotainment applications. It can better deal with the highly dynamic nature of roads and highways. Meanwhile, the existing infrastructure of the cellular networks is unable to cope with the heavy traffic imposed mainly by videos. Thus, the cellular operators may leverage Roadside Untis (RSU) to offload video traffic and provide better quality of experience for vehicle customers. In this paper, we propose a pricing model that motivates RSU owners to cooperate with the cellular operators in order to offer better quality of experience (QoE) and offload substantial part of videos traffic from the cellular networks. The pricing model also motivates the vehicle owners to cooperate with the RSU to deliver contents to each other and aims to maximize RSU revenue and provide a wide range of QoS levels to the content providers in order to give them a degree of freedom to choose the suitable level of quality for their customers and based on their allocated budgets. We prove this problem is hard to solve, then we propose a lightweight greedy methods as alternative solutions. The conducted results show the efficiency of the proposed solutions and their ability to obtain results similar or so close to the optimal solutions. en_US
dc.language.iso en en_US
dc.title Revenue-driven video delivery in vehicular networks with optimal resource scheduling en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 200502746 en_US
dc.author.department Computer Science And Mathematics en_US
dc.description.embargo N/A en_US
dc.journal.volume 23 en_US
dc.article.pages 100215 en_US
dc.keywords RSU revenue en_US
dc.keywords Resource allocation en_US
dc.keywords Video on demand en_US
dc.keywords VANETs en_US
dc.identifier.doi https://doi.org/10.1016/j.vehcom.2019.100215 en_US
dc.identifier.ctation Al-Hilo, A., Ebrahimi, D., Sharafeddine, S., & Assi, C. (2020). Revenue-driven video delivery in vehicular networks with optimal resource scheduling. Vehicular Communications, 23, 100215. en_US
dc.author.email sanaa.sharafeddine@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S2214209619302621#aep-article-footnote-id1 en_US
dc.orcid.id https://orcid.org/0000-0001-6548-1624 en_US
dc.author.affiliation Lebanese American University en_US


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