# BSM-Data Reuse Model Based on In-Vehicular Computing
## 4 BSM Reuse Model: Our Proposal
### In-Vehicle Computing: Advantages  
Vehicles are getting more intelligent and well equipped. Emerging intelligent vehicles will possess sufficient storage and computing resources to perform tasks locally, thus reducing the network load and delays. Contemporary vehicles are capable of owning a computer inside, which is an industrial edge-computer that is designed to sustain the rigors of vehicular environments while capturing, storing, and analyzing data from various sensors and devices required for Intelligent Transportation System applications. In-Vehicle Computing will then become paramount to substitute the classical Vehicle Cloud Computing (VCC). Table 3 highlights the differences between IVC and VCC according to different features. In addition, the key advantages of IVC can be summarized, as follows.  
* Storage: ncontrary to the centralized topology, the IVC permits the data storage inside the vehicle in the vicinity of their source of generation. This provides timely access to stored data and decreses the remot storage load.
* Bandwidth: in the era of the connected vehicle, the amount of generated data is growing explosively and the content demands will further become varied. When considering the distance from users in centralized topology, cloud computing cannot assure the bandwidth requirements for delivering and remote processing of such a large amount of data. By mounting the computation and storage resources on vehicles, IVC is able to properly mitigate the high-bandwidth pressure.
* Response Time: processing time with delivery time together represent the response time. In the case of centralized topology, the response time is considerable due to the delivery delay. In our decentralized topology IVC, the mounted computer as processing units is inside vehicle. Thus, the took responding time is significantly less, which enables connected vehicles to respond with more efficiency, better service, and further innovation through new applications.
* Contextual data: in decentralized topology, users are able to obtain real-time information related to the behavior and location of vehicles, traffic conditions, network environment, etc. Accordingly, different applications would be improved. For instance, real-time information can be delivered to various vehicular users in accordance with their interests.  
In accordance with the foregoing and taking advantage of the emerging Vehicle-mounted computing technology, we propose our IVC-based model, which relies on data storage, and processing inside the vehicle and that can definitely help to address the costs of bandwidth and enable more efficient real-time applications that require fast processing and response.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Features** & **In-Vehicle Computing** & **Vehicle Cloud Computing** \\ \hline Latency & Very Low & High \\ \hline Deployment cost & Low & High \\ \hline Communication & Real Time & Bandwidth Constrained \\ \hline Location & Close proximity to end-user & Remote location \\ \hline Decision making & Local & Centralized and Remote \\ \hline Burden on core network & Low & High \\ \hline Computation Capability & Medium & High \\ \hline Storage Capacity & Limited & Highly Scalable \\ \hline Mobility support & High & Limited \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison between In-Vehicle Computing (IVC) and Vehicle Cloud Computing (VCC).