skip to main content
10.1145/2342356.2342432acmconferencesArticle/Chapter ViewAbstractPublication PagescommConference Proceedingsconference-collections
research-article
Free Access

Optimizing cost and performance for content multihoming

Published:13 August 2012Publication History

ABSTRACT

Many large content publishers use multiple content distribution networks to deliver their content, and many commercial systems have become available to help a broader set of content publishers to benefit from using multiple distribution networks, which we refer to as content multihoming. In this paper, we conduct the first systematic study on optimizing content multihoming, by introducing novel algorithms to optimize both performance and cost for content multihoming. In particular, we design a novel, efficient algorithm to compute assignments of content objects to content distribution networks for content publishers, considering both cost and performance. We also design a novel, lightweight client adaptation algorithm executing at individual content viewers to achieve scalable, fine-grained, fast online adaptation to optimize the quality of experience (QoE) for individual viewers. We prove the optimality of our optimization algorithms and conduct systematic, extensive evaluations, using real charging data, content viewer demands, and performance data, to demonstrate the effectiveness of our algorithms. We show that our content multihoming algorithms reduce publishing cost by up to 40%. Our client algorithm executing in browsers reduces viewer QoE degradation by 51%.

Skip Supplemental Material Section

Supplemental Material

sigcomm-viii-03-optimizingcostandperformanceforcontentmultihoming.mp4

mp4

79.7 MB

References

  1. 01box. http://cdn.01box.net.Google ScholarGoogle Scholar
  2. V. K. Adhikari, Y. Guo, F. Hao, M. Varvello, V. Hilt, M. Steiner, and Z.-L. Zhang. Unreeling netflix: Understanding and improving multi-CDN movie delivery. In IEEE INFOCOM'12.Google ScholarGoogle Scholar
  3. H. A. Alzoubi, S. Lee, M. Rabinovich, O. Spatscheck, and J. Van Der Merwe. A practical architecture for an anycast CDN. ACM Trans. Web, 5(4):17:1--17:29, Oct. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. D. Beaver, S. Kumar, H. C. Li, J. Sobel, and P. Vajgel. Finding a needle in haystack: Facebook's photo storage. In USENIX OSDI'10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. G. Bertrand, E. Stephan, G. Watson, T. Burbridge, P. Eardley, and K. Ma. Use cases for CDNi. IETF Draft, Jan. 2012.Google ScholarGoogle Scholar
  6. D. Bertsekas. Convex Analysis and Optimization. 2003.Google ScholarGoogle Scholar
  7. CDN expert. http://cdnexpertonline.com/node/45.Google ScholarGoogle Scholar
  8. Cisco Systems. Cisco Visual Networking Index: Forecast and Methodology, 2011--2016.Google ScholarGoogle Scholar
  9. Conviva. http://www.conviva.com.Google ScholarGoogle Scholar
  10. F. Dobrian, V. Sekar, A. Awan, I. Stoica, D. Joseph, A. Ganjam, J. Zhan, and H. Zhang. Understanding the impact of video quality on user engagement. In ACM SIGCOMM'11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Dyn CDN manager. http://dyn.com/.Google ScholarGoogle Scholar
  12. Geo best-of YouTube. http://geobestofyoutube.gmapify.fr/.Google ScholarGoogle Scholar
  13. D. Goldenberg, L. Qiu, H. Xie, Y. R. Yang, and Y. Zhang. Optimizing cost and performance for multihoming. In ACM SIGCOMM'04. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. A. Ioffe and V. Tihomirov. Theory of Extremal Problems. Elsevier Science Ltd, 1979.Google ScholarGoogle Scholar
  15. R. Krishnan, H. V. Madhyastha, and etc.. Moving beyond end-to-end path information to optimize CDN performance. In ACM IMC'09. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Level 3 Intelligent Traffic Management. http://www.level3.com/ /media/Assets/brochures/brochure_intelligent_traffic_management.pdf.Google ScholarGoogle Scholar
  17. Limelight Traffic Load Balancer. http://www.limelight.com/traffic-load-balancer/.Google ScholarGoogle Scholar
  18. H. H. Liu, Y. Wang, Y. R. Yang, H. Wang, and C. Tian. Optimizing cost and performance for content multihoming. Technical Report YaleCS-TR1456, May 2012.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. MetaCDN. http://www.metacdn.com/.Google ScholarGoogle Scholar
  20. B. Niven-Jenkins, F. L. Faucheur, and N. Bitar. Content distribution network interconnection problem statement. IETF Draft, Jan. 2012.Google ScholarGoogle ScholarCross RefCross Ref
  21. OnePica. http://www.magentocommerce.com.Google ScholarGoogle Scholar
  22. R. S. Peterson and E. G. Sirer. Antfarm: efficient content distribution with managed swarms. In NSDI'09. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. R. S. Peterson, B. Wong, and E. G. Sirer. A content propagation metric for efficient content distribution. In ACM SIGCOMM'11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. I. Poese, B. Frank, B. Ager, G. Smaragdakis, and A. Feldmann. Improving content delivery using provider-aided distance information. In IMC'10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. T. Ristenpart, E. Tromer, H. Shacham, and S. Savage. Hey, you, get off of my cloud: Exploring information leakage in third-party compute clouds. In ACM CCS'09. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. N. H. Sleumer. Output-sensitive cell enumeration in hyperplane arrangements. Nordic J. of Computing, 6:137--147, June 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. XDN. http://www.xdn.com.Google ScholarGoogle Scholar

Index Terms

  1. Optimizing cost and performance for content multihoming

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      SIGCOMM '12: Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
      August 2012
      474 pages
      ISBN:9781450314190
      DOI:10.1145/2342356

      Copyright © 2012 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 August 2012

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      Overall Acceptance Rate554of3,547submissions,16%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader