# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 4 Challenges
### Integration of Communication and Computation  
The advancements in mobile cloud computing, distributed data storage, and vehicular communication technologies have played a significant role in the modeling and implementation of cooperative vehicle infrastructure systems. CVs possess onboard units that provide storage, communication, and computation functionalities, which allow these vehicles to offer cloud computing services to other connected mobile devices within their ranging scope [128]. This has given rise to innovative vehicular cloud computing from mobile cloud computing [129; 130], which has received increasing attention in recent years. In this paradigm, a cooperative small-scale cloudlet is established using inter-vehicle communication between vehicles and infrastructure. Thereby, vehicles are able to offload their different computation tasks to RSUs or central cloud data centers, or they may also utilize the computing resources available within vehicles in near proximity. Other cloud computing models have been deployed to assist intelligent CVs such as cloud computing software updates and training powerful deep learning algorithms [97]. The dynamic nature of CVs poses a significant challenge regarding the practical implementation and scalability of cooperative computation. This is in addition to the unique characteristics and limitations of vehicular networks, such as fast channel fading, deterioration that may result from Doppler effects, and many others that might affect the \begin{table}
\begin{tabular}{c c c} \hline \hline
**Application Name** & **Description** & **References** \\ \hline RLVW & Drivers are informed if they are about to cross a red light. & [73; 74; 75; 78] \\ \hline EEBL & Data is sent to alert drivers of hard braking performed by the vehicle in front of them. & [80; 81; 82; 83; 84] \\ \hline CSW & Drivers are notified that they are about to enter a curve with high speed & [85; 86; 87; 89] \\ \hline Platooning & Vehicles/trucks maintain inter-vehicle distances and are synced (speed, routes, and braking) to achieve enhanced fuel consumption & [90; 91; 92; 94] \\ \hline Infotainment & Commercial/entertainment applications & [96] \\ \hline Vehicle as a mobile service & Providing of other services beyond safety and entertainment such as localization or commercialization. & [4; 97; 98] \\ \hline Data monetization & Monetizing data to provide new innovative services. & [99; 100; 101; 102; 103; 104; 105] \\ \hline Last-mile delivery & Tackles efficient delivery of packages/parcels & [107; 108; 109; 110; 111; 112; 113; 114; 115; 116; 117] \\ \hline Smart intersection & Intersection signalized and non-signalized intersections to increase efficiency and decrease traffic delays. & [118; 119; 120; 121; 122; 123; 124; 125] \\ \hline Collaboration of smartphone applications with the vehicle & Integrating smartphone applications to aid in some of vehicle’s functionality such as replacing keys with smartphone application. & [126; 127] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Examples of Potential CVs Applications. reliability and efficiency of the transmitted data, for instance, when sending music or video files between vehicles and between vehicles and infrastructure [128]. As a consequence, computation performance in terms of reliability and efficiency is also greatly affected. This adds to the cloud-computation processing limitations, such as long processing times and high volumes of transmitted data. High latency in cloud computing relies on the wireless channel status, the network bandwidth, and the traffic congestion, thus hindering efficient real-time and reliable processing [97]. Further research is needed in designing robust and efficient vehicular cloud computation models in highly dynamic vehicular environments such as the open vehicular data analytics platform [131] and CAVBench [132] to address the QoS requirements of safety critical applications in real time. These vehicular applications require low latency and high reliability, along with secure and private data transmission.