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Enabling Contribution Awareness in an Overlay Broadcasting System
ACM SIGCOMM 2006 Presented by He Yuan
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Outline Background Related Work Contribution-aware Design
Implementation and Experiments Conclusion Discussion
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Video Broadcast using Overlay Multicast
Encoder E Boston D E Pisa D D: DSL E: Ethernet D San Francisco Tokyo E LA Overlay Tree Boston NYC Pisa LA San Francisco Tokyo
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Background I State-of-Art in Overlay Broadcast
Architecture and Protocol Design Narada, SplitStream, CoopNet, DONet ... Significant progress in scalability & resiliency Real Deployments ESM*, CoolStreaming, PPLive, SopCast ...
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Background II Much success to date:
Homogeneous environments with abundant bandwidth Heterogeneity in node upload bandwidth Upload access bandwidth varies widely Hosts may choose to forward differently Insufficient bandwidth resource Download Upload DSL Kbps 64-256Kbps Cable 1-6Mbps Kbps Ethernet ≥ 10Mbps > 80% < 20%
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Related Work Bit-for-bit policy Differential Admission Control
Effective only in BT-like systems Differential Admission Control Not feasible in the mainstream Internet Taxation model Incentive vs. Fairness
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Goals and Challenges Goals Challenges Good utilization of bandwidth
Differential and equitable distribution Guaranteed QoS Challenges More generic than bit-for-bit policy Distributed sampling and computing Dynamic environment
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Contribution-aware Design
Assumptions Multi-tree-based data dissemination Bandwidth distribution policy System design
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Assumptions Abundant download bandwidth
Different levels of contribution Actual contribution fi reflected by Forwarding bound Fi Non-strategic honest clients To encourage a host to relax its Fi
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Multi-tree-based data dissemination
Using MDC, split into T-equally sized stripes T trees, each distributes a single stripe of size S/T Overall quality depends on the number of stripes received Number of trees node i is entitled to = S Kbps Peer A Source Peer C S/3 S/3 S/3 Tree 1 Tree 2 Tree 3
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Bandwidth distribution policy
∑ fj / N j Entitled bandwidth Contribution 0 < α < 1 More generic than bit-for-bit Differential and Equitable Distribution
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Bandwidth distribution: Example
S = 400Kbps T = 4 avg f = 300Kbps α = 0.5 fE = 500Kbps fD = 100Kbps rE = 0.5* *300 = 400Kbps entitled to 4 trees rD = 0.5* *300 = 200Kbps entitled to 2 trees Entitled Node Source Excess Node 100Kbps 100Kbps 100Kbps 100Kbps E D D E E D E D
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System Design Distributed System Sampling
Computing Number of Entitled Trees Smoothing Locating Excess Bandwidth Backoff in Excess Tree Contribution-Aware Node Prioritization
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Implementation and Experiments
Use Slashdot to evaluate 2 systems: Cont-Agnostic: multi-tree broadcast system Cont-Aware: multi-tree + contribution-aware heuristics S=400Kbps, T=4, stripe size S/T=100Kbps 2 types of peers: Ethernet fmax ≤800Kbps, DSL fmax ≤100Kbps HC: Kbps, LC: Kbps Broadcast Event DSL (100Kbps) Ethernet (10Mbps) Peak Group Size SIGCOMM2002 48% 52% 78 SOSP2003 54 Rally 75% 25% 481 Slashdot 73% 27% 158 GrandChallenge 82% 18% 276 Conferences Mainstream Internet
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Evaluation Goals Fairness Overall quality of playback Stability
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Performance: High Contributors
System Mean Std. Dev Cont-Agnostic 353 60.9 Cont-Aware 415 24.6 Better Cont-Aware gives HC better performance
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Performance: Low Contributors
Better System Mean Std. Dev Cont-Agnostic 311 80.5 Cont-Aware 295 34.8 Better Similar performance among similar contributors
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Stability Time between Tree Reductions Reconnection time (in sec)
Cont-Aware performs slightly worse Reductions => slight dips in quality Not complete disconnection, 63.4% from 43, 34.1% from 32, only 2.5% from 21 and 10 Reconnection time (in sec) Cont-Aware Cont-Agnostic HC 7.1 80.82 LC 53.42 65.26 Overall 48.25 69.83
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Performance across traces for high contributors
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Conclusion Resource-scarce, heterogeneous environments
Two key ideas: Multi-trees and Linear Taxation Provide fairness in overlay broadcasting in mainstream Internet environments
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Discussion Applying MDC to Multi-tree overlay
The issue of redundancy in coding What’s different in the resulting system? More bandwidth resource or Better QoS Incentive or fairness Where to go? Customized user requirement - Demand according to capacity Location-aware streaming reuse technique
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Thanks!
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