<p>IoV is a known platform for exchanging data between vehicles and distinct networks through diverse communication media. Embedded technologies like IoT and Intelligent Transportation, are aimed to build smart networks for IoV to support diverse automated applications such as smart vehicle control, intelligent traffic control, and dynamic data services. However, in the smart domain, implementation of IoV has unresolved challenges. Synchronization of vehicles and humans is a crucial issue in making decisions. Therefore, proper understanding of the pertinent issues about IoV implementation that can improve the VNs performance are essential. DSRC and cellular networks are considered as potential alternatives for endorsing V2X communications. DSRC is employed for intelligent and automotive transportation applications through short-range data exchange between DSRC-components. Although spectrum assigned to DSRC alone will not be appropriate to satisfy huge information traffic needs for internet access in vehicles. Cellular networks offer potential solutions, attributing extensive range of cell coverage, broadly deployed infrastructure and greater capacity. Nevertheless, centralized characteristics of these networks limit the ability to handle low-latency communications that can challenge the efficacy of several safety applications. This paper reviews potential DSRC and wireless integrated solutions for efficient vehicular communications. In methodology, first we reviewed existing technologies that integrate DSRC with other wireless technologies and secondly, the study is carried out to highlight the limitations for each supporting vehicular communications. Thereby, the paper embeds a brief comparative analysis. Finally, an algorithm is proposed to integrate DSRC and 4G-LTE with a novel Optimal Clustering based Data Forwarding Protocol for efficient data transmission to attain better performance in IoV. The performance of the proposed algorithm is compared with the existing approaches using the NS-3 simulation tool. The obtained results demonstrate that the proposed algorithm outperforms over the existing approaches in terms of End to End Delay and throughput. </p>