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BALANCING THROUGHPUT, ROBUSTNESS, AND IN-ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie Mellon University, †Intel Labs Pittsburgh Presented by Haoming Fu
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Page 1: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

BALANCING THROUGHPUT, ROBUSTNESS, AND IN-ORDER DELIVERY IN P2P VODBin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki †Carnegie Mellon University, †Intel Labs Pittsburgh

Presented by Haoming Fu

Page 2: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

INDEX

INTRODUCTION TRS TRADEOFF BALANCING THE TRADEOFF EVALUATION CONCLUSION

Page 3: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

1, INTRODUCTION

P2P Background Important Metrics VOD Goals

Page 4: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

P2P BACKGROUND

P2P file transfer: Bit Torrent, Emule VoD(Video on Demand): PPLive Live Streaming: 中大网络电视 (no terminal

software, centralized solution?)

Features of VoD: Demand sequentiality for playback while

downloading chunks. Desire short buffering time but not low downloading time.

Less synchrony, permit longer buffering time(though not desired), jump & skip.

Page 5: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

IMPORTANT METRICS

(T)hroughtput: the number of bytes downloaded per second

(R)obustness: the ability to maintain high throughput in face of network conditions such as node failure, arrival/departure and heterogeneity of users’ bandwidth.

(S)equentiality: the order of chunk arrival.

What we actually want is: high sequential throughput with tolerable robustness.

Page 6: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

VOD GOALS

Useful chunks: a subset of chunks in a contiguous sequence from the start of the file.

Useful chunks

Page 7: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

VOD GOALS

Buffer time

Out of buffer

Slope: playback rate

Page 8: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

2, TRS TRADEOFF

Model Assumptions and Metrics Definitions & Assumptions Throughput Robustness Sequentiality

Three Basic Schemes Tradeoff Theorem

Page 9: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

DEFINITIONS & ASSUMPTIONS

Downlink capacity is not bottleneck. Leave once a node has all chunks. Steady state: #the rate of departures =

#the rate of new arrivals, thus the population size of the swarm is stable.

Bandwidth allocation: Seed and peers allocate their uplink bandwidth capacity uniformly among the chunks that they are serving.chunk 1 3 4 8

chk 1 2 4 5 7 8 10

bandwidth

Page 10: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

DEFINITIONS & ASSUMPTIONS

Ci: the sum of the share of the uplink bandwidth allocated for chunk i from the seed and all other peers.

Page 11: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

THROUGHPUT

It’s safe to assume there is only one seed in the swarm since seeds are homogeneous(同质的 ).

gi: the seed allocates a fraction gi of its uplink bandwidth to chunk i.

fi: on average a peer allocates fi.

Page 12: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

THROUGHPUT

Theorem 1: for a system in steady state,

b: chunk size : maximal arrival rate

Proof:

Steady state: Qi(T)/T is the rate of replicating chunk i, which

is bounded by the per-chunk capacity Ci/b. Therefore < <=Ci/b, for all i.

num of chunk i’s copies

peers go

peers come

Page 13: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

THROUGHPUT

By eq.(1) and eq.(2), we have

Chunk k is the bottleneck chunk. Apply a little law: to eq.(3), we have

T is the average downloading time.

Page 14: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

THROUGHPUT

Applying Theorem 1, N= T, We get the lower bound for T,

Page 15: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

ROBUSTNESS

denotes the probability of a peer being “bad”(e.g. slow; failing)

ri be the number of available sources that each peer can download chunk i from

Intuitively, it is the probability of having at least one good source to download from.

Page 16: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

ROBUSTNESS

In steady state, the probability for a randomly selected peer to have x chunks is 1/M, for x = 0;1;…; M-1.

the expected number of chunks that a random peer has downloaded is

R’s upper bound:

Total number of chunks

Page 17: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

SEQUENTIALITY

useful chunksDenote U(x) as the fraction of useful chunks given x downloaded chunks.

0 <= S <= 1

e.g U(400) = 300/400

Page 18: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

2, TRS TRADEOFF

Model Assumptions and Metrics Three Basic Schemes

Rarest Random Naive(幼稚的 ) Sequential Cascading(瀑布 )

Tradeoff Theorem

Page 19: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

RAREST RANDOM

The probability for a peer that has downloaded x chunks to have any particular chunk i is x/M.

BT

Throughput

Apply theorem 1, we have

Lower bound! Perfect throughput.

Page 20: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

RAREST RANDOM

Robustness

Thus,

Upper bound! Perfect robustness.

Sequentiality Completely no sequentiality.

#num of peers having x chunks

#pro of having chunk i

Page 21: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

NAIVE SEQUENTIAL

Note, only peers with i, i+1, …, M chunks have chunk i.

In steady state, the number of peers with 0, 1, …, M-1 chunks is N/M.

Throughput CM is contributed only by

seeds.

CM is bottleneck, & Naive Sequential is unstable.

Page 22: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

NAIVE SEQUENTIAL

Robustness

Sequentiality

Page 23: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

CASCADING

Highest throughput, if the seed is not the bottleneck, the downloading time is

Lowest robustness, intuitively, when one link breaks down, the whole

chain collapses.

Fully sequentiality.

Page 24: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

2, TRS TRADEOFF

Model Assumptions and Metrics Three Basic Schemes Tradeoff Theorem

Page 25: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

TRADEOFF THEOREM

Theorem 2. A P2P VoD system can not simultaneously maximize throughput, robustness and sequentiality.

Proof Assume otherwise. Maximized T:

Maximized S: a seed has i, then has i-1, …, 1 Maximized R: serve all the chunks it has i < j, then Ci < Cj, contradiction!

Page 26: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

3, BALANCING THE TRADEOFF

Hybrid Strategy Segment Random Many More in the Space

Page 27: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

HYBRID STRATEGY

Combine rarest first and naive sequential. download a chunk according to naive

sequential with pro , according to random with 1-s.

higher s improves sequentiality but may reduce the system throughput.

grey: x

xsx(1-s)

Page 28: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

HYBRID STRATEGY

Discussion: bandwidth division1. Downlink capacity d, playback rate q. d > q.Download sequentially at rate q, while

randomly at d-q?When q/d 1, it degenerate to NS.

2. Dynamic scheme. With enough useful chunks buffered, s is low?

Useful chunks buffered not enough s increase low throughput further not enough s increase …

Page 29: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

SEGMENT RANDOM

The Segment random strategy groups all M chunks of the file into K segments, each of which consists of W chunks.

Segments in order Chunks random

chunk

segment

Page 30: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

SEGMENT RANDOM

peers downloading chunks in the last segment can help upload this last segment.

W large, RF K large, NS

Page 31: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

4, EVALUATION

Experiment Setup TRS Tradeoff in Emulation Buffering Time

Page 32: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

EXPERIMENT SETUP

1 seed, 50 peers 10 Mbps up, 20 Mbps down, 10 ms latency For robustness measurement, “bad” nodes:

heterogeneous nodes (one third are significantly slower: 2 Mbps up and 5 Mbps down)

Page 33: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

TRS TRADEOFF IN EMULATION

high throughput

7.33, robust

awful seq

Page 34: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

BUFFERING TIME

Only when sequential throughput is high, can the buffering time become low.

beautiful aweful

Page 35: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

5, CONCLUSION

TRS Tradeoff Theorem.

Page 36: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

THANK YOU!

Any questions, remarks or objections?

Page 37: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

RAREST RANDOM

The chunks are uniformly distributed among peers, thus the probability for a peer that has downloaded x chunks to have any particular chunk i is x/M. (BT)

chunk i obtains 1/x of the uplink bandwidth if it has been downloaded already (with probability x/M) 0 with pro 1-x/M

Page 38: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

RAREST RANDOM

Throughput

, we have

Apply theorem 1, we have

Lower bound! Perfect throughput.

Page 39: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

RAREST RANDOM

Robustness

In steady state, peers are downloading equally rapidly so the number of peers having x chunks (x = 0;1;…;M-1) is N/M, we have

Thus,

Upper bound! Perfect robustness.

Page 40: BALANCING THROUGHPUT, ROBUSTNESS, AND IN- ORDER DELIVERY IN P2P VOD Bin Fan, David G. Andersen, Michael Kaminsky†, Konstantina Papagiannaki † Carnegie.

RAREST RANDOM

Sequentiality

We have,

Completely no sequentiality.


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