CoGenT: A Content-oriented Generative-hit Framework for Content Delivery Networks

TL;DR

CoGenT introduces a framework that leverages edge computing and data generation to improve CDN performance by reducing latency and bandwidth usage, especially in missing data scenarios.

Contribution

It proposes a novel content-oriented generative-hit framework (CoGenT) that uses idle edge resources to generate data, enhancing CDN efficiency beyond traditional caching.

Findings

Reduces average access latency by half in real-world tests.

Enhances existing caching algorithms, lowering latency and bandwidth.

Confirmed effectiveness through simulation experiments.

Abstract

The service provided by content delivery networks (CDNs) may overlook content locality, leaving room for potential performance improvement. 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 (CoGenT) for CDNs. CoGenT utilizes idle computing resources on edge nodes to generate requested data based on similar or related cached data to achieve hits. Our implementation in a real-world system demonstrates that CoGenT reduces the average access latency by half. Additionally, experiments conducted on a simulator also confirm that CoGenT can enhance existing caching algorithms, resulting in reduced latency and bandwidth usage.