Characteristics of YouTube network traffic at a campus network - Measurements, models, and implications

  • Authors:

  • Michael Zink;Kyoungwon Suh;Yu Gu;Jim Kurose

  • Affiliations:

  • Department of Computer Science, University of Massachusetts, Amherst, MA 01003, United States;School of Information Technology, Illinois State University, Normal, IL 61790, United States;Department of Computer Science, University of Massachusetts, Amherst, MA 01003, United States;Department of Computer Science, University of Massachusetts, Amherst, MA 01003, United States

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2009

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Abstract

User-Generated Content has become very popular since new web services such as YouTube allow for the distribution of user-produced media content. YouTube-like services are different from existing traditional VoD services in that the service provider has only limited control over the creation of new content. We analyze how content distribution in YouTube is realized and then conduct a measurement study of YouTube traffic in a large university campus network. Based on these measurements, we analyzed the duration and the data rate of streaming sessions, the popularity of videos, and access patterns for video clips from the clients in the campus network. The analysis of the traffic shows that trace statistics are relatively stable over short-term periods while long-term trends can be observed. We demonstrate how synthetic traces can be generated from the measured traces and show how these synthetic traces can be used as inputs to trace-driven simulations. We also analyze the benefits of alternative distribution infrastructures to improve the performance of a YouTube-like VoD service. The results of these simulations show that P2P-based distribution and proxy caching can reduce network traffic significantly and allow for faster access to video clips.