# QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing
## 2 Literature Review
### Scheduling SDVN Models  
Scheduling is the process of allocating tasks/messages for communication to take place in order. As the local SDN control receives multiple messages, such scheduling mechanisms must manage and send messages based on priority. In some cases, we need to send essential data earlier than the already received messages for transmission, so in this situation, we need such scheduling that gives proper priority to messages and then transmits it based on the attached priorities. In [17], the author proposed the Unmanned Aerial Vehicle (UAV) model. The proposed model is infrastructure-less and based on SDN technology. The author provided a theoretical offloading mechanism in which they offload data based on different levels of zones. Emergency zone data are sent first, then the other zone data, and so on. The main aspect of the proposed model is to keep a balance between energy consumption and communication delay. Similarly, in [18], the author proposed a priority-based scheduling algorithm called the RSA algorithm tapping vigorous cloud. The proposed model divides the data into emergency data, and least used data, urgent data, and the average user data. They further send the data according to the scheduling algorithms such as CFFS, NDS, and SJF. The proposed model performed well in terms of energy consumption and bandwidth, as shown in the results. In [19], the authors proposed scheduling algorithm-based deadlines and size. If any task/message deadline and size is less than the model, send that data first, and so on. They provided D*S Algorithm by sending vehicle messages to RSU. The proposed model calculates message priority based on deadline and size. In [20], they proposed a collective scheduling algorithm in which they categorized messages into three categories: the size of messages, static factor, and dynamic factor. Static messages are divided into safety and no safety messages, while dynamic messages are calculated from VANET clustering. From the results of the provided mechanism, energy consumption is decreased and performed well. [PERSON] et al. [21] proposed the Hybrid Emergency Message Transmission (HEMT) model by using SDN technology. Similarly, ref. [22] proposed a cloud-based scheduling model. The proposed model is based on the nature of data such as video, audio, and text. In [23; 24], the authors proposed a mobility-aware scheduling algorithm by sending and receiving vehicle messages in the concerned cluster circle. The authors of [25] proposed a Markov-based model while giving high priority to high mobility vehicles. Similarly, in [26], the author proposed a packet-based scheduling algorithm by using a multi-level queuing system. Another scheduling algorithm is provided in which the authors proposed a scheduling model and gave high priority to the packets whose deadline is near to expire. In [27; 28], the authors recently proposed efficient architecture for SDVN by using a priority basis scheduling algorithm for time-critical and non-critical messages. Its main limitation is that they did not use fog instead of cloud to decrease response time, and they also did not use a fault tolerance mechanism to make the overall process of SDVN communication efficient. Furthermore, in [29], the author proposed vehicle to vehicle, vehicle to infrastructure communication for congestion avoidance. They used linear adaptive congestion control designed for leveraging the performance of VANET communication. They did not use a fault tolerance mechanism for data offloading and fog for data processing to reduce delay as compared with the proposed model. Similarly, in [30] the author proposed QoS aware vehicle communication model using the clustering technique. They reduced packet drop ratio and messages delay. They did not use nearby edge devices for processing to reduce the further delay of the messages.