CGHit: A Content-Oriented Generative-Hit Framework for Content Delivery Networks
Peng Wang, Yu Liu, Kai Han, Ziqi Liu, Peng Liu, Mingyang Wang, Ke Zhou, Zhihai Huang · 2024
The service provided by content delivery networks (CDNs) may overlook content locality, leaving the potential to improve performance. In this study, we explore the feasibility of leveraging generated data as a replacement for fetching data in missing scenarios based on content locality. Due to sufficient local computing resources and reliable generation efficiency, we propose a content-oriented generative-hit framework (CGHit) for CDNs. CGHit utilizes idle computing resources on edge nodes to generate requested data based on similar or related cached data, achieving hits. Extensive experiments in a real-world system demonstrate that CGHit reduces the average access latency by half. In addition, experiments conducted on a simulator confirm that CGHit can enhance current caching algorithms, leading to lower latency and reduced bandwidth usage.