1 / 28

Proxy Cache Management for Fine-Grained Scalable Video Streaming

Proxy Cache Management for Fine-Grained Scalable Video Streaming Jiangchuan Liu The Chinese University of Hong Kong Xiaowen Chu and Jianliang Xu Baptist University of Hong Kong Infocom’04, March 2003 Outline Introduction and Motivations Problem Settings and Solutions

andrew
Télécharger la présentation

Proxy Cache Management for Fine-Grained Scalable Video Streaming

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. Proxy Cache Management for Fine-Grained Scalable Video Streaming Jiangchuan Liu The Chinese University of Hong Kong Xiaowen Chu and Jianliang Xu Baptist University of Hong Kong Infocom’04, March 2003

  2. Outline • Introduction and Motivations • Problem Settings and Solutions • Performance Evaluation and Comparison • Conclusion and Future Work

  3. Video Caching • Proxy caching saving video objects at proxies close to clients • Temporal locality • Geographical locality

  4. Unique Features Video objects vs. Web objects • High data rate, yet adaptive • Long playback duration ► Various interactions: • random access • early termination ► Huge volume • one-hour MPEG-1, about 675 MB

  5. r2 r1 r2 r1 2 3 1 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 Partial Caching • Interval caching (Dan96, Tewari98…) • Prefix caching (Sen99, Jin02…) • Segment caching (Wu01, Miao02, Chae,Chen03…)

  6. Common Assumptions • Continuous playback • No interactions or premature termination • Homogeneous segment access rate • Homogeneous clients • Identical access bandwidth • Time partitioning only • Non-adaptive caching • Non-scalable single-rate video

  7. Our Assumptions and Objectives • Assumptions • User interactivity: early terminations • Heterogeneous client access bandwidths • Vehicle • Fine-Grained Scalable (FGS) video • Objectives • Rate adaptive caching and streaming • Understanding the benefits (?) of FGS caching • Vs. Replication (Hartanto02), Transcoding (Tang02)

  8. Related Work and Differences cut-off rate • Video staging (Zhang00) • Quality adaptation (Yu00, Rejaie00) • Adaptation per user basis • Replacement • Prefetching • Blocking performance (Kangasharju02) • Admission control • Homogeneous access rate • Caching for VCR-operations (Fahmi01)

  9. Outline • Introduction and Motivations • Problem Settings and Solutions • Performance Evaluation and Comparison • Conclusion and Future Work

  10. System Model and Operations

  11. Model Parameters

  12. Problem(1): Caching Strategy • Explore the rate adaptability of FGS in caching • Problem: • Given cache size and client utility level, which portion of an FGS video should be cached • Objective • Min transmission cost • Difficulty: • Heterogeneous bandwidth demands • Non-uniform segment access rate • A 2-D space: time and rate • Greedy is not optimal

  13. Problem(1): Solution • 2-segment • Exhaustive search • Multi-segment • Access probability – segment/rate

  14. Problem (2): Utility Assignment • Explore the rate adaptability of FGS in both caching and streaming • Problem • Given cache size and backbone bandwidth limits, jointly decide the caching strategy and utility assignment of each client. • Objective • Max expected client utility , , , ,

  15. Problem(2): Iterative Solution • Difficulty • Utility assignment  optimal caching strategy (problem 1) • Caching strategy  optimal utility assignment (dynamic programming) • Iterative optimization • 2-Segment – exhaustive search on cache partition

  16. Optimization for Multiple Objects • Heterogeneity of objects • Access rate • Access bandwidth • Client distribution • Cache partitioning • Backbone Bandwidth partitioning • 2-D Knapsack • Pseudo-polynomial partitioning algorithm

  17. Outline • Introduction and Motivations • Problem Settings and Solutions • Performance Evaluation and Comparison • Conclusion and Future Work

  18. Sample Configuration • Client • Multiple classes • Uniform, skewed • Utility function • Linear • 2-segments: early termination • Probability = 0.3 • A conservative configuration !

  19. Backbone Bandwidth Reduction • MaxLen: length first • MaxRate: rate first

  20. Joint Optimal Caching & Utility Assignment

  21. Results for Multiple Videos • Baseline • uniform cache partition + proportional bandwidth partition

  22. Scalable Video or Replicated Video? • Optimal caching for replicated video • 1D knapsack • Backbone bandwidth reduction with FGS

  23. Scalable Video or Transcoding ? Given a frame interval of 30 ms, our PC can support about 300 concurrent filter/assembler operations

  24. Outline • Introduction and Motivations • System Description • Problem Settings and Solutions • Performance Evaluation and Comparison • Conclusion and Future Work

  25. Conclusion • FGS-based proxy caching • Key problems • Optimal caching strategy • Optimal utility assignment • Optimization for multiple videos • Performance Evaluation • Backbone bandwidth reduction • Utility improvement • Comparision • FGS caching vs. Replication caching • FGS filtering vs. Transcoding

  26. Future Work • Utility functions • Tradeoff: accuracy/speed • Multi-segments • Fastforward, backward • Practical issues • Error control • Synchronization • Signaling

  27. Thanks Q & A

  28. Scalable Video or Replicated Video? • Utility improvementwith FGS

More Related