1 / 28

Optimizing Cost and Performance for Content Multihoming

Optimizing Cost and Performance for Content Multihoming. SIGCOMM’12 -Piggy, 2013.03.18. Outline. What is Content Multihoming Goal Control Framework Global Optimization Local Adaptation Evalution. Content Multihoming. CDN Diversity. CDN DIVERSITY. CDN DIVERSITY. Goal.

afia
Download Presentation

Optimizing Cost and Performance for Content Multihoming

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Optimizing Cost and Performance for Content Multihoming SIGCOMM’12 -Piggy, 2013.03.18

  2. Outline • What is Content Multihoming • Goal • Control Framework • Global Optimization • Local Adaptation • Evalution

  3. Content Multihoming

  4. CDN Diversity

  5. CDN DIVERSITY

  6. CDN DIVERSITY

  7. Goal • Algorithms and protocols that optimize • Content publisher cost • Content viewer performance • A content object can be delivered from multiple CDNs, which CDN(s) should a content viewer use?

  8. Notation

  9. Control Framework

  10. Passive vs. Active Client • Passive client • Use one CDN edge server at a time • Active client • Adaptation algorithm • Multiple CDN servers for a single content object

  11. Problem Statement (Q) • QoEguarantee • CDN k is providing the required features to deliver content object i • exceeds the performance target • Cost optimization • Balance load to multiple CDNs to minimize total cost

  12. Active Client • Virtual CDN • Primary CDN • Backup CDN • k’ = (k, j)

  13. Computing Optimization(CMO) • Problem Q has an optimal solution which assigns a location object into a single CDN • K|A|N

  14. Basic Idea

  15. Extension • CDN subscription levels • Fix fee to different usage levels • Different levels as an individual CDN • Per-request cost • Extend vector dimension to R+1 • Multiple streaming rates • Independent content objects

  16. Local Adaptation • QoE protection • Prioritized guidance • Low session overhead

  17. Local Adaptation • Similar to TCP AIMD • Total workload control • Priority assignment

  18. Evaluation Setting

  19. Cost Saving

  20. Cost Saving

  21. Active Client Setting • Clients • 500+ Planetlab nodes with Firefox 8.0 + Adobe Flash 10.1 • Two CDNs • Amazon CloudFront • CDN3

  22. Active Client Test Case

  23. Stress Tests (Step-down)

  24. Stress Tests (Ramp-down)

  25. Stress Tests (Oscillation)

  26. Active Client QoE Gain

  27. Conclusion • We develop and implement a two-level approach to optimize cost and performance for content multihoming: • CMO: an efficient algorithm to minimize publisher cost and satisfy statistical performance constraints • Active client: an online QoE protection algorithm to follow CMO guidance and locally handle network congestions or server overloading

  28. Q&A

More Related