Emergent Mind

Named Data Networking for Content Delivery Network Workflows

(2010.12997)
Published Oct 24, 2020 in cs.NI

Abstract

In this work we investigate Named Data Networking's (NDN's) architectural properties and features, such as content caching and intelligent packet forwarding, in the context of a Content Delivery Network (CDN) workflows. More specifically, we evaluate NDN's properties for PoP (Point of Presence) to PoP and PoP to device connectivity. We use the Apache Traffic Server (ATS) platform to create an HTTP, CDN-like caching hierarchy in order to compare NDN with HTTP-based content delivery. Overall, our work demonstrates that properties inherent to NDN can benefit content providers and users alike. Our experimental results demonstrate that HTTP is faster under stable conditions due to a mature software stack. However, NDN performs better in the presence of packet loss, even for a loss rate as low as 0.1%, due to packet-level caching in the network and fast retransmissions from close upstreams and fast retransmissions from close upstreams. We further show that the Time To First Byte (TTFB) in NDN is consistently lower than HTTP (~100ms in HTTP vs ~50ms in NDN), a vital requirement for CDNs, in addition to supporting transparent failover to another upstream when a failure occurs in the network. Moreover, we examine implementation agnostic (implementation choices can be Software Defined Networking, Information Centric Networking, or something else) network properties that can benefit CDN workflows.

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.