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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

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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
Outline
  • Introduction and Motivations
  • Problem Settings and Solutions
  • Performance Evaluation and Comparison
  • Conclusion and Future Work
video caching
Video Caching
  • Proxy caching

saving video objects at proxies close to clients

    • Temporal locality
    • Geographical locality
unique features
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
partial caching

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…)
common assumptions
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
our assumptions and objectives
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)
related work and differences
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)
outline9
Outline
  • Introduction and Motivations
  • Problem Settings and Solutions
  • Performance Evaluation and Comparison
  • Conclusion and Future Work
problem 1 caching strategy
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
problem 1 solution
Problem(1): Solution
  • 2-segment
    • Exhaustive search
  • Multi-segment
    • Access probability – segment/rate
problem 2 utility assignment
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

,

,

,

,

problem 2 iterative solution
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
optimization for multiple objects
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
outline17
Outline
  • Introduction and Motivations
  • Problem Settings and Solutions
  • Performance Evaluation and Comparison
  • Conclusion and Future Work
sample configuration
Sample Configuration
  • Client
    • Multiple classes
    • Uniform, skewed
  • Utility function
    • Linear
  • 2-segments: early termination
    • Probability = 0.3
    • A conservative configuration !
backbone bandwidth reduction
Backbone Bandwidth Reduction
  • MaxLen: length first
  • MaxRate: rate first
results for multiple videos
Results for Multiple Videos
  • Baseline
    • uniform cache partition + proportional bandwidth partition
scalable video or replicated video
Scalable Video or Replicated Video?
  • Optimal caching for replicated video
    • 1D knapsack
  • Backbone bandwidth reduction with FGS
scalable video or transcoding
Scalable Video or Transcoding ?

Given a frame interval of 30 ms, our PC can support about 300 concurrent filter/assembler operations

outline24
Outline
  • Introduction and Motivations
  • System Description
  • Problem Settings and Solutions
  • Performance Evaluation and Comparison
  • Conclusion and Future Work
conclusion
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
future work
Future Work
  • Utility functions
  • Tradeoff: accuracy/speed
    • Multi-segments
    • Fastforward, backward
  • Practical issues
    • Error control
    • Synchronization
    • Signaling
thanks
Thanks

Q & A

scalable video or replicated video28
Scalable Video or Replicated Video?
  • Utility improvementwith FGS