A survey on the state-of-the-art CDN architectures and future directions

Abstract

A Content Delivery Network (CDN) consists of a distributed infrastructure of proxy servers designed to deliver digital content to end users effectively. CDNs have gained popularity due to increasing Internet users and their growing demand for low-latency content delivery. However, several unexplored aspects within CDN technology, including management, standardization, and architecture of CDNs, are crucial to staying aligned with industry trends and advancements. Previous survey papers focus on CDN aspects and have not yet categorized state-of-the-art CDN architectures. In this survey, we categorize and analyze seven state-of-the-art CDN architectures, providing a detailed analysis of their components, benefits, and limitations. We highlight advancements such as the convergence of CDN and Content-Centric Networking (CCN) paradigms for improved data retrieval, fog-based CDN collaboration with MEC for edge processing optimization, and blockchain technology for secure content delivery. Additionally, we also identify research challenges within CDN architectures and discuss the effectiveness of proposed solutions. Finally, we propose future research directions, including the collaboration of reinforcement learning for adaptive edge responses in CDN-P2P, machine learning for CDN selection in multi-CDN setups, and federated learning for improved caching in software-based and fog-based CDNs.