Next Article in Journal
Interactive, Multiscale Urban-Traffic Pattern Exploration Leveraging Massive GPS Trajectories
Previous Article in Journal
Avoiding 3D Obstacles in Mixed Reality: Does It Differ from Negotiating Real Obstacles?
Open AccessArticle

Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration

1
Department of Computer and Information Security, Sejong University, Seoul 05006, Korea
2
Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang 37673, Korea
3
Department of Computer Science and Engineering, National Institute of Technology, Andhra Pradesh 534101, India
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(4), 1092; https://doi.org/10.3390/s20041092
Received: 23 December 2019 / Revised: 11 February 2020 / Accepted: 13 February 2020 / Published: 17 February 2020
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’ use cases. View Full-Text
Keywords: cloud-based vehicular network; virtualization; cloud computing; software-defined vehicular cloud network; multi-access edge cloud; vehicular cloud; virtual machine migration cloud-based vehicular network; virtualization; cloud computing; software-defined vehicular cloud network; multi-access edge cloud; vehicular cloud; virtual machine migration
Show Figures

Figure 1

MDPI and ACS Style

Nkenyereye, L.; Nkenyereye, L.; Adhi Tama, B.; Reddy, A.G.; Song, J. Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration. Sensors 2020, 20, 1092. https://doi.org/10.3390/s20041092

AMA Style

Nkenyereye L, Nkenyereye L, Adhi Tama B, Reddy AG, Song J. Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration. Sensors. 2020; 20(4):1092. https://doi.org/10.3390/s20041092

Chicago/Turabian Style

Nkenyereye, Lionel; Nkenyereye, Lewis; Adhi Tama, Bayu; Reddy, Alavalapati G.; Song, JaeSeung. 2020. "Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration" Sensors 20, no. 4: 1092. https://doi.org/10.3390/s20041092

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop