Abstract
Vehicular edge networks (VENs) connect vehicles to share data and infotainment content collaboratively to improve network performance. Due to technological advancements, data growth is accelerating, making it difficult to always connect mobile devices and locations. For vehicle-to-vehicle (V2V) communication, vehicles are equipped with onboard units (OBU) and roadside units (RSU). Through back-haul, all user-uploaded data is cached in the cloud server's main database. Caching stores and delivers database data on demand. Pre-caching the data on the upcoming predicted server, closest to the user, before receiving the request will improve the system's performance. OBUs, RSUs, and base stations (BS) cache data in VENs to fulfill user requests rapidly. Pre-caching reduces data retrieval costs and times. Due to storage and computing expenses, complete data cannot be stored on a single device for vehicle caching. We reduce content delivery delays by using the cuckoo search optimization algorithm with cooperative content caching. Cooperation among end users in terms of data sharing with neighbors will positively affect delivery delays. The proposed model considers cooperative content caching based on popularity and accurate vehicle position prediction using K-means clustering. Performance is measured by caching cost, delivery cost, response time, and cache hit ratio. Regarding parameters, the new algorithm outperforms the alternative.