Cooperative Content Caching Framework Using Cuckoo Search Optimization in Vehicular Edge Networks

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.

Efficient V2V Communications by Clustering-Based Collaborative Caching

“…Kind Description [4] Collaborative caching CHs receive content from RSU; CMs receive content from both of them [12] Collaborative caching Vehicles broadcast alternately [5] Collaborative caching A vehicle preferentially requests content from others moving in the same lane [13] Collaborative caching A vehicle decides whether to cache content based on the vehicle's power, the content's popularity, the gain acquired by the content, and the distance (hop count) to the content provider [14] Collaborative caching Both vehicles and RSUs construct clusters [15] Collaborative caching Vehicles within an RSU are divided into clusters, and they send requests to the RSU [16] Collaborative caching…”

“…Some research has applied existing algorithms to V2V communications, e.g., a cuckoo search for route calculation [15], the 0-1 knapsack problem for cache decisions [16], and the Minimum Weight Vertex Cover Problem for cache placement [20].…”