{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T06:31:24Z","timestamp":1772087484634,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,2,17]],"date-time":"2020-02-17T00:00:00Z","timestamp":1581897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Cloud computing supports many unprecedented cloud-based vehicular applications. To improve connectivity and bandwidth through programmable networking architectures, Software- Defined (SD) Vehicular Network (SDVN) is introduced. SDVN architecture enables vehicles to be equipped with SDN OpenFlow switch on which the routing rules are updated from a SDN OpenFlow controller. From SDVN, new vehicular architectures are introduced, for instance SD Vehicular Cloud (SDVC). In SDVC, vehicles are SDN devices that host virtualization technology for enabling deployment of cloud-based vehicular applications. In addition, the migration of Virtual Machines (VM) over SDVC challenges the performance of cloud-based vehicular applications due the highly mobility of vehicles. However, the current literature that discusses VM migration in SDVC is very limited. In this paper, we first analyze the evolution of computation and networking technologies of SDVC with a focus on its architecture within the cloud-based vehicular environment. Then, we discuss the potential cloud-based vehicular applications assisted by the SDVC along with its ability to manage several VM migration scenarios. Lastly, we provide a detailed comparison of existing frameworks in SDVC that integrate the VM migration approach and different emulators or simulators network used to evaluate VM frameworks\u2019 use cases.<\/jats:p>","DOI":"10.3390\/s20041092","type":"journal-article","created":{"date-parts":[[2020,2,20]],"date-time":"2020-02-20T03:20:03Z","timestamp":1582168803000},"page":"1092","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration"],"prefix":"10.3390","volume":"20","author":[{"given":"Lionel","family":"Nkenyereye","sequence":"first","affiliation":[{"name":"Department of Computer and Information Security, Sejong University, Seoul 05006, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8871-4299","authenticated-orcid":false,"given":"Lewis","family":"Nkenyereye","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Security, Sejong University, Seoul 05006, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1821-6438","authenticated-orcid":false,"given":"Bayu","family":"Adhi Tama","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang 37673, Korea"}]},{"given":"Alavalapati","family":"Reddy","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, National Institute of Technology, Andhra Pradesh 534101, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2157-9651","authenticated-orcid":false,"given":"JaeSeung","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Security, Sejong University, Seoul 05006, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,17]]},"reference":[{"key":"ref_1","unstructured":"Intelligent transport systems (2019, December 31). 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