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dc.contributor.author Sami, Hani
dc.contributor.author Mourad, Azzam
dc.contributor.author El-Hajj, Wassim
dc.date.accessioned 2021-04-08T14:23:50Z
dc.date.available 2021-04-08T14:23:50Z
dc.date.copyright 2020 en_US
dc.date.issued 2021-04-08
dc.identifier.issn 1063-6692 en_US
dc.identifier.uri http://hdl.handle.net/10725/12675
dc.description.abstract Observing the headway in vehicular industry, new applications are developed demanding more resources. For instance, real-time vehicular applications require fast processing of the vast amount of generated data by vehicles in order to maintain service availability and reachability while driving. Fog devices are capable of bringing cloud intelligence near the edge, making them a suitable candidate to process vehicular requests. However, their location, processing power, and technology used to host and update services affect their availability and performance while considering the mobility patterns of vehicles. In this paper, we overcome the aforementioned limitations by taking advantage of the evolvement of On-Board Units, Kubeadm Clustering, Docker Containerization, and micro-services technologies. In this context, we propose an efficient resource and context aware approach for deploying containerized micro-services on on-demand fogs called Vehicular-OBUs-As-On-Demand-Fogs. Our proposed scheme embeds (1) a Kubeadm based approach for clustering OBUs and enabling on-demand micro-services deployment with the least costs and time using Docker containerization technology, (2) a hybrid multi-layered networking architecture to maintain reachability between the requesting user and available vehicular fog cluster, and (3) a vehicular multi-objective container placement model for producing efficient vehicles selection and services distribution. An Evolutionary Memetic Algorithm is elaborated to solve our vehicular container placement problem. Experiments and simulations demonstrate the relevance and efficiency of our approach compared to other recent techniques in the literature. en_US
dc.language.iso en en_US
dc.title Vehicular-OBUs-As-On-Demand-Fogs en_US
dc.type Article en_US
dc.description.version Published en_US
dc.title.subtitle Resource and Context Aware Deployment of Containerized Micro-Services en_US
dc.author.school SAS en_US
dc.author.idnumber 200904853 en_US
dc.author.department Computer Science And Mathematics en_US
dc.relation.journal IEEE/ACM Transactions on Networking en_US
dc.journal.volume 28 en_US
dc.journal.issue 2 en_US
dc.article.pages 778-790 en_US
dc.keywords Containers en_US
dc.keywords Cloud computing en_US
dc.keywords Automobiles en_US
dc.keywords Computer architecture en_US
dc.keywords Performance evaluation en_US
dc.keywords Delays en_US
dc.keywords Task analysis en_US
dc.identifier.doi https://doi.org/10.1109/TNET.2020.2973800 en_US
dc.identifier.ctation Sami, H., Mourad, A., & El-Hajj, W. (2020). Vehicular-OBUs-as-on-demand-fogs: Resource and context aware deployment of containerized micro-services. IEEE/ACM Transactions on Networking, 28(2), 778-790. en_US
dc.author.email azzam.mourad@lau.edu.lb
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/abstract/document/9032323 en_US
dc.orcid.id https://orcid.org/0000-0001-9434-5322 en_US
dc.author.affiliation Lebanese American University en_US

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