# BSM-Data Reuse Model Based on In-Vehicular Computing
## 2 Related Works
In addition, they are not scalable data collection for a given coverage and budget constraints [11; 12]. Despite that the authors of [10] have adopted the Information-Centric Networking (ICN) concept, in their work, the information importance remains location-based, depends on the content popularity and computed through the observation of the amount and frequency of user interests it received, where they neglected whether the receiver is satisfied or not with this content. Moreover, there is no proper metric to classify and identify the participants' eligibility that has been used by the authors of [11]. In [12], the proposed deployment strategy can notably be influenced by large-scale mobility model and road layout. In regards to data transmission works, the centralized model presented in [13] is limited to single-hop V2V communication and do not match by the SDN concept of \"logically centralized\" control in a distributed network. In [14], although the authors have respected the recommended latency requirements for CV applications, they considered in their experimentation latency that only includes the delivery time of a message and not the processing times, such as the time required for aggregation and complex data transformation. The proposed infrastructure presented in [16] is not extendable to any network size, so it is not capable to support Internet-enabled content distribution. Though the mobility model and road vehicle density can deadly influence the intra-cluster message dissemination, they have not been considered in the clustering process in [17]. The authors of [18] have described the generation process and outlined the impact of the generated dataset on the simulative evaluation of vehicular networks. Nevertheless, a real-world dataset remains necessary to allow for a more rigorous validation of the mobility models. On the data side, not all previous work used realistic, reliable, and large-scale data sources, such as BSMs; each system instead has defined its proprietary data formats and collected its required data to provide its services. Consequently, different applications in these systems are not able to complement each other by reuse and sharing data, as they are unable to understand each other's data. This hinders cross-application data reuse and optimizations (e.g., to reduce data traffic by reducing redundancy). On the simulation side, some works were concerned by a local simulation area [11; 13; 15; 16; 17], a limited sample [14], and an unknown number [10] of simulated vehicles with limited buffer size [10; 15]. The communication characteristics were not specified in [10; 11; 16; 18] and simulated based only on DSRC technology in [12; 13; 14]. Besides, advances in vehicular communications technology are making content sharing within vehicular networks more effective and increasingly more popular [19]. Some other works have explored the potential of interworking between DSRC and cellular network technologies for efficient V2X communications in favor of data sharing. The work presented by [20] has investigated the possibility of leveraging DSRC and cellular interworking for successful V2X transmissions and examined possible DSRC and cellular combined architectures. Another study in [21] has taken advantage of the potential of V2X communications based on LTE technology to introduce a device-to-device content-sharing approach. V2V and V2I link planning take into account both data diversity and link quality. As can be seen, notwithstanding that connected vehicle data have recently got in the limelight of the research community, many of the previous and on-going researches have focused on the concept of data collection and sharing, yet the reuse of data has not been in focus. Notably, BSM reuse, which is of salient importance, has been disregarded in previous researches. In addition, the realities of data reuse are not yet straightforward.