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Layered Peer-to-Peer Streaming Yi Cui, Klara Nahrstedt Department of Computer Science University of Illinois at Urbana-Champaign Source International Workshop.

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Presentation on theme: "Layered Peer-to-Peer Streaming Yi Cui, Klara Nahrstedt Department of Computer Science University of Illinois at Urbana-Champaign Source International Workshop."— Presentation transcript:

1 Layered Peer-to-Peer Streaming Yi Cui, Klara Nahrstedt Department of Computer Science University of Illinois at Urbana-Champaign Source International Workshop on NOSSDAV’03, June, 2003

2 Outline Problem addressing  Asynchronous  Heterogeneity Layered peer-to-peer streaming solution  Unlimited number of supplying peers  Constraint supplying peers  Layered rate heterogeneity Performance evaluation Conclusion

3 Problem addressing Asynchronous  User request media data at different time  Solution: cache-and-relay approach Heterogeneity  Request stream of different qualities due to resource constraints such as network bandwidth  Solution: layer-encoded streaming approach

4 Problem addressing (cont.)

5 Layered peer-to-peer streaming Feature  Limited inbound/outbound bandwidth Goal  Maximize total qualities  Subject to Q k : total receive layers of peer k I k : inbound bandwidth O k : outbound bandwidth H k : peers

6 Layered peer-to-peer streaming l k : inbound bandwidth of H k (# of layers) A k : available layers at the cache of H k H 0 : server, S = { H 1, H 2, …, H M } : set of hosts sorted by available layer number i.e., A 1 ≤ A 2 ≤ … ≤ A M Q k m : # of layers get from host m Q k : streaming quality

7 Basic algorithm (cont.)

8 Basic algorithm Available cache layersOutbound bandwidth H1H1 H2H2 H3H3 H4H4 HkHk Get from server ! Allocate maximum # of layers for H k

9 Enhanced algorithm C k : constraint on maximum # of supplying peers Q k *(M, C k ): optimal solution if H k can only choose C k supplying peers from H 1 ~H M Q max (H m+1, …, H M ): best contributor in { H m+1, …, H M } Maximize total receive data at H k DP implementation ─ O(C k M 2 )

10

11 Fault tolerance Normal departure  Due to user logout or quality degradation  The departure peer notifies H k to reconfigure Fail  Due to machine crash or network failure  Either temporally request from server or suffer from quality degradation

12 Fault tolerance (cont.) Available cache layersOutbound bandwidth H1H1 H2H2 H3H3 H4H4 HkHk Access from server or degradation !

13 Layered rate heterogeneity Layer rate allocation schemes  Natural Number Scheme l 0 = r 0, r k = k ‧ r 0  Exponential Scheme r k = r 0 ‧ 2 k  Fibonacci Scheme r 1 = 2r 0, r k = r k-1 + r k-2

14 Layered rate heterogeneity (cont.) r i : streaming rate of layer I (Kbps) I k, O k : inbound and outbound bandwidth (Kbps)

15 Performance evaluation peers  Modem/ISDN: 50%, 112Kbps (max)  Cable Modem/DSL: 35%, 1Mbps (max)  Ethernet peers: 15%, 10Mbps (max) 60-min video, which consists of 50 layers, with full quality streaming rate = 1Mbps Run 24 hours

16 Overall streaming quality and scalability Streaming quality satisfaction = Q k /I k

17 Tradeoff between overall quality & constrained supplying peers

18 Fairness

19 Robustness

20 Layer rate heterogeneity

21 Conclusion Introduce a layered peer-to-peer streaming approach to optimize the streaming quality of heterogeneous peers, save server bandwidth. Hope to make best use of bandwidth resource of supplying peers. Evaluate the solution by:  Test fairness among peers according to streaming quality satisfaction and bandwidth contribution.  Test robustness against unexpected departures/fails.


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