Abstract
This editorial is an outgrowth of our research efforts that resulted in the SIGCOMM'93 paper [1] entitled
On the self-similar nature of Ethernet traffic.
We discuss some lessons we have learned as we have watched the published findings being absorbed by the scientific community in general and the networking community in particular. We focus on aspects that have remained relevant today, especially at a time when, with the proliferation of Artificial Intelligence and Machine Learning, networking research has become increasingly data-dependent and data-driven.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Software
Reference46 articles.
1. On the self-similar nature of Ethernet traffic
2. On the self-similar nature of Ethernet traffic (extended version)
3. NSF. The launch of the NSFNET. https://web.archive.org/web/20170202190224/ https://www.nsf.gov/about/history/nsf0050/internet/launch.htm NSF. The launch of the NSFNET. https://web.archive.org/web/20170202190224/ https://www.nsf.gov/about/history/nsf0050/internet/launch.htm
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