on peer-to-peer media streaming dongyan xu mohamed heffeda susanne hamrusch bharat bhargava 2002...
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On Peer-to-Peer Media Streaming
Dongyan Xu
Mohamed Heffeda
Susanne Hamrusch
Bharat Bhargava
2002 International Conference on Distributed Computing Systems
Outline
Introduction P2P Media Streaming Model Optimal Media Data Assignment Fast System Capacity Amplification Simulation Conclusion
IntroductionCategory of P2P system
Main difference between a general P2P system and a P2P media system is the data sharing mode
– Open-after-downloading mode– Play-while-downloading mode
IntroductionCharacteristics of a P2P media system
Self-growingThe more peers it serves , the larger the capacity it will have
Server-lessSuch as opening a large number of simultaneous connection
HeterogeneousDifferent out-bound bandwidth contribution to the system
IntroductionCharacteristics of a P2P media system
Many-to-oneMultiple supplying peers in one real-time streaming session
IntroductionProblems of P2P media system
Media data assignment for a multi-supplier peer-to-peer streaming session
Fast amplification of the P2P streaming capacity
P2P Media Streaming Model
Roles of peersEach supplying peer participates in at most one P2P streaming session at any time
Bandwidth of peers
– R0 : denote the playback rate of the media data
– Rin(Pr) = R0
– Rout(Ps) = R0/2n (R0/2 , R0/4 , …. R0/2N)
P2P Media Streaming Model
Classes of peers– Classify the peers into N classes according to their
out-bound bandwidth offer– Class-n peer : offer out-bound bandwidth R0/2n (1
n N )≦ ≦ Capacity of the P2P streaming system
Segments of media data– Media data be partitioned into small sequential
segments of equal sizes– δt of each segment is the same
Optimal Media Data Assignment
Bad CaseRequesting peer : Pr
Supplying peers : P1s , P2
s , P3s , P4
s ( R0/2 , R0/4 , R0/8 , R0/8) P1
s : 8k+1 , 8k+2 , 8k+3 , 8k+4
P2s : 8k+4 , 8k+5
P3s : 8k+6
P4s : 8k+7
( k = 0, 1, 2, 3, …. )
Optimal Media Data Assignment
Optimal CaseRequesting peer : Pr
Supplying peers : P1s , P2
s , P3s , P4
s ( R0/2 , R0/4 , R0/8 , R0/8)
(1) The lowest class among supplying peer is class-n
(2) Computes the assignment of the first 2n segments
Optimal Media Data Assignment
The algorithm OTSp2p compute an optimal media data assignment achieves the minimum buffering delay
The minimum buffering delay
Fast System Capacity Amplification
Waiting time : interval between requesting peer first streaming request and the earliest time it can be admitted
T : duration of the P2P streaming session
Class-1 : P3s , P4
s , P3r
Class-2 : P1s , P2
s , P1r, P2
r
Average waiting time
(0+T+2T)/3 = T
Fast System Capacity Amplification
Average waiting time
(T+T+0)/3 = 2T/3
•Different admission decisions lead to different growth of streaming capacity
•Higher-class requesting peers will lead to a faster amplification of the system capacity
Fast System Capacity AmplificationDistributed admission control protocol (DACp2p)
Key features– Supplying peer can decides whether or not
to participate in a streaming session by probability
– Requesting peer may send a reminder to a busy supplying peer Ps
Fast System Capacity AmplificationDACp2p – Supplying Peers
Each Ps maintains an admission probability vector <Pr[1] , Pr[2], ..Pr[N]>
How to determine probability vector
1. Suppose Ps is class-k peerPr[i] = 1.0 when 1 i k≦ ≦Pr[i] = 1/2i-k when k<i N≦class i is favored class of Ps , if Pr[i] =1.0
2. If Ps idle , then probability vector will be updated after a period of Tout
k < i N, Pr[i] = Pr[i]*2≦
Fast System Capacity AmplificationDACp2p – Supplying Peers
(3) If Ps finished serving a streaming , will update its probability vector
During the streaming session , did not receive any request of its favored classk < i N, Pr[i] = Pr[i]*2≦
If received one request of its favored class , request peer left a reminder to Ps , if k is the highest favored class of requesting peer which left a reminder Pr[i] = 1.0 when 1 i k≦ ≦Pr[i] = 1/2i-k when k<i N≦
Fast System Capacity AmplificationDACp2p – Requesting Peers
Pr obtains a list of M randomly supplying peers , and directly contact the candidate from high to low classes
Pr will be admitted– Pass the probabilistic admission test– Rsum = R0
Pr will be rejected – Pr will leave a reminder to a busy Ps who currently
favors the class of Pr
– Backoff for at least a period of Tbkf befor making the request again
Simulation
Number of requesting peers : 50000 Number of seed supplying peers : 100 Each seed peers is a class-1 peer Show time of video : 60 min Class distribution of requesting peers
class-1 : 10%class-2 : 10%class-3 : 40%class-4 : 40%
M = 8 Tout = 20 min Tbkf = 10 min Simulate period : 144 hours During the first 72 hours , the 50000 peers make their first
streaming requests
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