Dynamic Cache Management In Content Delivery Networks

TL;DR

This paper introduces an online, low-complexity, optimization-based cache management algorithm for CDNs that adapts to changing content popularity and outperforms existing caching methods in various metrics.

Contribution

It presents a novel incremental online algorithm for content placement in CDNs that is near-optimal and handles dynamic popularity without demand estimation.

Findings

Outperforms state-of-the-art caching techniques on synthetic data.

Effective in handling time-varying content popularity.

Proven near-optimal storage allocations.

Abstract

The importance of content delivery networks (CDN) continues to rise with the exponential increase in the generation and consumption of electronic media. In order to ensure a high quality of experience, CDNs often deploy cache servers that are capable of storing some of the popular files close to the user. Such edge caching solutions not only increase the content availability, but also result in higher download rates and lower latency at the user. We consider the problem of content placement from an optimization perspective. Different from the classical eviction-based algorithms, the present work formulates the content placement problem from an optimization perspective and puts forth an online algorithm for the same. In contrast to the existing optimization-based solutions, the proposed algorithm is incremental and incurs very low computation cost, while yielding storage allocations that are provably near-optimal. The proposed algorithm can handle time varying content popularity, thereby obviating the need for periodically estimating demand distribution. Using synthetic and real IPTV data, we show that the proposed policies outperform all the state of art caching techniques in terms of various metrics.