TY - GEN
T1 - Named Data Networking for Content Delivery Network Workflows
AU - Thelagathoti, Rama Krishna
AU - Mastorakis, Spyridon
AU - Shah, Anant
AU - Bedi, Harkeerat
AU - Shannigrahi, Susmit
N1 - Funding Information:
This work is partially supported by a pilot award from the Center for Research in Human Movement Variability and the NIH (P20GM109090), Tennessee Tech Faculty Research Grant, and the National Science Foundation (awards 2016714, 2019163, and 2019012).
Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/9
Y1 - 2020/11/9
N2 - 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 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 a CDN-like caching hierarchy in order to compare NDN with HTTP-based content delivery. Overall, our work demonstrates that several properties inherent to NDN can benefit content providers and users alike through in-network caching of content, fast retransmission, and stateful hop-by-hop packet forwarding. Our experimental results demonstrate that HTTP delivers content 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. 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. Unlike HTTP, NDN also supports transparent failover to another upstream when a failure occurs in the network. Finally, we present implementation-agnostic (implementation choices can be Software Defined Networking, Information Centric Networking, or something else) network properties that can benefit CDN workflows.
AB - 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 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 a CDN-like caching hierarchy in order to compare NDN with HTTP-based content delivery. Overall, our work demonstrates that several properties inherent to NDN can benefit content providers and users alike through in-network caching of content, fast retransmission, and stateful hop-by-hop packet forwarding. Our experimental results demonstrate that HTTP delivers content 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. 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. Unlike HTTP, NDN also supports transparent failover to another upstream when a failure occurs in the network. Finally, we present implementation-agnostic (implementation choices can be Software Defined Networking, Information Centric Networking, or something else) network properties that can benefit CDN workflows.
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U2 - 10.1109/CloudNet51028.2020.9335806
DO - 10.1109/CloudNet51028.2020.9335806
M3 - Conference contribution
AN - SCOPUS:85100709864
T3 - Proceedings - 2020 IEEE 9th International Conference on Cloud Networking, CloudNet 2020
BT - Proceedings - 2020 IEEE 9th International Conference on Cloud Networking, CloudNet 2020
A2 - Caicedo Rendon, Oscar Mauricio
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Cloud Networking, CloudNet 2020
Y2 - 9 November 2020 through 11 November 2020
ER -