# Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration
## 5 Conclusions  
In this paper, we summarize our findings along with lessons learned collected from our study on the state-of-the art accomplishment of SDVC-related cloud-vehicular applications and their VM management with other technologies (e.g., fog computing, Follow-Me cloud/edge, and vehicular cloud) for offering cloud-based vehicular applications. Based on the many substantial research works we reviewed, academia and industry are proposing design and configurations of SDVC architectures that would support cloud-vehicular applications. Therefore, efficient resource management, low cost VM migrations and processing latency, are stringent requirements for delivering cloud-based applications. Although various VM migrations strategies have been proposed in vehicular cloud computing, the extensive investigation to evaluate the effectiveness of VM migration management of the SDVC remains an open issue. The researchers envision the use of SDVCs coupled with other technologies such as edge/fog computing and NFV. The control layer of SDVC would play an important role in the management of computing resources. In addition, research directions should focus on the implementation of intelligent selection algorithms to run inside the control layer of the SDN controllers in SDVC. For VM machine migration, when the vehicle decides to migrate the service, the MEC may require the SDN controller to choose the most suitable MEC server to start the service migration process. The SDN controller should be able to estimate the potential cost incurred and compare it against the resource utilization modules designed to improve the MEC cost and QoS from the point of view of end users. VM migration process in SDVC architecture can be further modeled using existing VM strategies discussed and implemented as applications that consider QoE requirements. The selection algorithms based on SDN concept would help to produce the best routing policy to decide whether to migrate a service or not. QoS-aware mobility multi-access selection algorithm; selection algorithm of migration path with both cost; resource allocation on multi-access edge servers; development of a high service migration mechanism for inter-MEC migration case, intra-MEC VM migration case, and micro-data computing across MEC; and central cloud to ensure service continuity are considered as research directions. In addition, an emulation platform for evaluating QoS and routing applications of SDVC applications is missing. The real traffic mobility using SUMO, for instance, might be included to evaluate the simulation of SD-based vehicular cloud applications. To support a range of unprecedented cloud-based vehicular applications that improve connectivity and bandwidth of cloud-based applications, SDVC is introduced. SDVC architecture considers vehicles to host virtualization services for enabling a VM to migrate from one RSU to another. In addition, we studied the evolution of computation and networking technologies of SDVC with a focus on its architecture within the cloud-based vehicular environment. Then, we discussed the potential cloud-based vehicular applications assisted by the SDVC along with its ability to manage multiple VM migrations. We also provided a detailed comparison of existing frameworks in SDVC that integrate the VM migration approach and different emulator or simulator networks used to evaluate VM frameworks' use cases. In future work, we aim to provide further evaluation of discussed schemes based on their theoretical concepts and their performance. We will also consider the network resource slicing at the multi-access edge computing cloud for densely deployed vehicular network scenarios. Conceptualization, L.N. ([PERSON]); methodology, L.N. ([PERSON]); validation, J.S. and L.N. ([PERSON]); writing--original draft preparation, L.N. ([PERSON]) and L.N. ([PERSON]); writing--review and editing, L.N. ([PERSON]) and A.G.R. ; supervision, B.A.T. and J.S. ; and funding acquisition, J.S. All authors have read and agreed to the published version of the manuscript.