# Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration
## 4 Migration Management of VM over SDVC
### Review of the State-of-the-Art of VM Migration Techniques over SDVC
#### 4.2.2 Simulation Tools for VM Migration Services over SDVC
Strategies for service migration such as Follow-Me Edge, pre-copy  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline \multirow{2}{*}{**Strategies for VMM**} & **Mobility** & **Vehicular** & **Cost on** & **Fog** & **Migration** & **SDN** & **Reduce** & **Follow** & **Resources** \\  & **Prediction** & **Cloud** & **VMM** & **RSU** & **Computing** & **Policies** & **Concept** & **Failures** & **Management** \\ \hline MyiFogSim [60] & \(\surd\) & & \(\surd\) & \(\surd\) & & & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Fellow-Me & & & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) & \\ Edge [61] & & & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline pre-copy & & & & & \(\surd\) & & & \(\surd\) & \(\surd\) \\ Live VM [62] & & & & & \(\surd\) & & & \(\surd\) & \(\surd\) \\ \hline proactive service & & & & & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) \\ replication [63] & \(\surd\) & & & & \(\surd\) & \(\surd\) & & \(\surd\) & \\ \hline VM-based & & & & & & & & \(\surd\) & \\ RSUCloudlet [4; 64] & & \(\surd\) & \(\surd\) & \(\surd\) & & & & \(\surd\) & \\ \hline MDP-based service & & & & & \(\surd\) & & \(\surd\) & & & \(\surd\) \\ Migration[49; 65] & \(\surd\) & & & \(\surd\) & & \(\surd\) & & & \(\surd\) \\ \hline Time window & & & & \(\surd\) & & \(\surd\) & & & \(\surd\) & \\ based Service & \(\surd\) & & & \(\surd\) & & & & \(\surd\) & \(\surd\) \\ Migration [66] &based Live VM, and location-based VMM are implemented in [61; 62; 69], respectively. Follow-Me Edge presents a concept that enables services to move across edge servers as per the movement directions of their respective users. This concept mitigates VM migration latency by leveraging migrations policies implemented at the edge servers. Furthermore, pre-copy based Live VM is designed to reduce both migration time and downtime. This approach relies on dynamic approach that executes a regression analysis based on the amount of dirty pages recorded previously to predict the downtime. The prediction of the downtime value is compared with a predefined downtime to determine the right stage to execute a movement into the stop and copy stage. The location-based VMM considers the fog computing paradigm and its features to keep processing of cloud based applications in the proximity of users. This strategy identifies business models to keep VM migration reliable, particularly as the mobile users move among fog servers. Some of the proposed business models are: Service Provider/Service Orientation, Support and service contracts, and All-in-one enterprise cloud [69]. Strategies for service migration in no vehicular environments depend on mobility prediction solutions to enhance fog computing resources and global network traffic. MyiFogSim evaluates resources allocation in fog computing assisted by a user mobility prediction strategy while a VM service is migrating among fog servers towards users's directions [60]. MyiFogSim simulator defines migration policies that examine when a user should be migrated and where the user's VM is going, i.e. the destination of fog and how the migration is handled. In [63], a proactive replication mechanism is introduced as a promising VM strategy to avoid QoE degradation during service migration between different edge nodes. The proactive replication is assisted by two linear optimization algorithms for replication-based service migration. Markov Decision Process (MDP)-based service migration is introduced in [65]. MDP is the analytical model used to evaluate the performance of the Follow-Me Controller (FMC) [49]. Hence, MDP model mainly focuses on finding the user equipment (UE) position regarding the optimal data center (DC). The time window based service migration aims to find the optimal service placement so that the average cost of VM migration over a given time would be minimized [66].