Internet of Vehicles (IoV) represents a groundbreaking advancement in vehicular networks, seamlessly connecting vehicles to the Internet to improve road safety, traffic efficiency, and overall driving experiences. However, this integration comes with significant challenges, including data offloading, clustering, resource allocation, and security concerns. This study provides a detailed exploration of the current state of research and innovation in the IoV domain, focusing on these four critical areas. It offers a thorough analysis of data offloading techniques that enable efficient data exchange between vehicles and edge computing infrastructures, enhancing service delivery, and minimizing delays. Additionally, the paper examines clustering strategies that organize vehicles into dynamically managed groups, improving data management and ensuring network scalability. Resource allocation methods are also reviewed to highlight how computational and network resources can be optimally utilized to maintain high-performance levels across IoV systems. Furthermore, the paper delves into security concerns such as data privacy, integrity, and access control, emphasizing the need for robust mechanisms to protect IoV communications against cyber threats. By synthesizing findings from recent research and industry practices, this survey identifies key research gaps, proposes future directions, and aims to support the development of more efficient, secure, and scalable IoV ecosystems. It is a step toward realizing a safer, smarter, and more connected future in vehicular technology.