1 / 10

Cloud Control with Distributed Rate Limiting

Cloud Control with Distributed Rate Limiting. Barath Raghavan, Kashi Vishwanath Sriram Ramabhadran, Kenneth Yocum & Alex C.Snoeren Offence: Alex Kiaie & Shiqi Chen. Problems and Flaws. Global Random Drop Longer estimate interval VS overhead What happened to GRD at last?

yana
Télécharger la présentation

Cloud Control with Distributed Rate Limiting

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. Cloud Control with Distributed Rate Limiting Barath Raghavan, Kashi Vishwanath Sriram Ramabhadran, Kenneth Yocum & Alex C.Snoeren Offence: Alex Kiaie & Shiqi Chen

  2. Problems and Flaws • Global Random Drop • Longer estimate interval VS overhead • What happened to GRD at last? • Central Token Bucket • Flow Proportional Share • Gossip Protocal • Exceeding limit • Evaluation on PlanetLab

  3. Global Random Drop • GRD definitely works better under shorter estimate interval, but how about the overhead generated by frequent communication?

  4. Global Random Drop • It seems this paper proposes GRD and drops it in the end without a good reason. • What’s the purpose of proposing GRD then? Only to show FPS sucks in maintaining fairness?

  5. Central Token Bucket • Seems the authors design everything to approximate the performance of CTB. So why don’t we just stick to CTB and keep life simple??

  6. Flow Proportional Share FTP works fine under Branch = 5 or 7 for 500 limiters. But as the performance for Branch = 1 worsens a lot when we have more than 400 limiters. What will the changing point be for Branch =5 or 7? Or should we abandon the Gossip Protocal?

  7. Flow Proportional Share We can see the FPS scheme is very ‘stable’ in 500-ms estimate interval condition. BUT why half of the time the aggregate rate is above the 10Mps limit??

  8. Flow Proportional Share • Evaluation on PlanetLab? • We’ve already doubted the credibility of PlanetLab for millions of times in this class… • And the evaluation scale is really small…

  9. Flow Proportional Share And we noticed some performance we did not see in previous evaluation result of stable implementations. How to explain this? Does it imply that there could be more problem with real network implementation?

  10. Thank you! • Any comment? Question?

More Related