Peer-Assisted Content DistributionPablo RodriguezChristos Gkantsidis

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Traditional Content Distribution

Often, large content needs to be distributed to millions of clients:

• Currently: • Huge server farms• Infrastructure-based

solutions (e.g. Akamai)

slow, expensive, non scalable

Server Farm

3

Content Distribution Evolution

Hype

Realism

Growth

CachingIP Multicast

CDNsAkamai

EnterpriseCDNs

Layer-7 SwitchesSatellite CDNs

P2P

1999

2000

2001

2002

2003

2004

Disappointment

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Peer-Assisted Content Distribution

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Peer-Assisted Content DistributionDesktop PCs can help each other!• Clients become new servers• Capacity increases with the

number of clients• Limitless scalability and fast

speeds at extremely low cost!!

Server Farm

10

100

1000

10000

100000

1000000

10000000

Time (sec)

Nu

mb

er

of

Clien

ts S

erv

ed

Cooperative

Client/Server

4 MB file. Server 100 Mbps. Client 1 Mbps

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Examples• Updates/Critical Patches

– Adding large servers and egress capacity to absorb pick load is quite expensive

– Alternative solution is to delay clients» Patches do not arrive on-time

• Software Distribution

• TV On-Demand. Movie/Music downloads

• PodCasting

• Enterprise content distribution

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P2P Content Distribution

• Benefits:– Dramatically improves speed– Limitless scalability– Minimum server requirements– Very cheap

• Challenges:– Requires incentives for cooperation– Hard to ensure end2end full connectivity– Security– Manageability– Lack of locality increases transit costs for ISPs– Asymmetric links (traffic engineering)– Variable bandwidth, peers come and go– Need for more sophisticated distribution algorithms

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P2P Swarming• File is divided into many small pieces for distribution • Clients request different pieces from the server or from other clients• Clients become servers for those pieces downloaded• When all pieces are downloaded, clients can re-construct the whole file

1 2 65

Server

3 4

1 5 6 2 4

1 2 3 4 5 6

3

[Rodriguez, Biersack, Infocom’00]

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1 2 65

The Challenge

Server

3 4

1 5 6 2 4

1 2 3 4 5 6

3

If there are many users,deciding which is the best piece to download can be very hard!! Incorrect decisions result in low

throughput, nodes not able to finish, bandwidth wasted, etc.

Solutions that require to have full knowledge of who has what are non-scalable

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Avalanche: Improving file swarming using Coding Techniques

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Goal

•Provide a very fast and robust Peer-Assisted solution for the distribution of legal content

•Current problems in existing File Swarming solutions:

•Rare-blocks are hard to obtain•Tit-for-tat incentive mechanisms decrease speeds•Arrival of new users slows down old users•Heterogeneous nodes do not interact well•Same information travels repeatedly over bottleneck links•Too much dependency from seeds•Sudden departures can prevent peers from finishing

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Source

The Problem of Efficient Scheduling of Information

Node A Node B

Block 1Block 2

Node C

Block 1

Block 1, or 2, or 12?

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The Avalanche Magic

• To solve problems of existing P2P file distribution solutions, Avalanche uses special encoding algorithms

• Each encoded piece has the “DNA” of all pieces in the file.=> A given encoded piece can be used by any peer in place of any piece

• Encoded pieces are created using linear equations that involve all pieces in the file

• Reconstructing the file requires collecting enough encoded pieces and solving the set of mathematical equations

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Coding in general• Assume file: F = [x1 x2], where xi is a block.

• Define code Ei(ai,1, ai,2) = ai,1*x1+ ai,2*x2, where ai,1, ai,2 are numbers.

• “Infinite” number of Ei’s.

• Any two linearly independent Ei(ai,1, ai,2) can recover [x1 x2]. – Similar as solving a system of linear equations.

• Operations in finite fields [such as GF(216)].

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Avalanche Coding

B1 B2 Bn

Server

1 2

Client A

1 2 n

E1 E2

Client B

1 2

E3

[Chou et al., ’03]

• Content is encoded at the server• Clients can produce new encoded packets out of partial files

n

File

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Avalanche Robustness

If server suddenly goes down (after serving the full file one), all Avalanche users are able to complete the download. Only 10% of users using typical file-swarming techniques are able to complete.

Typical file-swarming systems

Avalanche

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Avalanche Download Time

Fin

ish

Tim

es

Nodes (sorted by order of arrival)

AvalancheTypical swarming

Peers using typical file-swarming

techniques that did not finish.

=> Much lower and predictable download times

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No need for nodes to stay around…

• With Avalanche, there is no need for nodes to stay after they finish the download to help other nodes (the performance remains unchanged)

Nodes stay for ever

Nodes leave immediately

Nodes (sorted by order of arrival)

Fin

ish

Tim

es

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Minimum Server Requirements

Less than half the server requirements compared to systems based on current file-swarming techniques.

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Decoding Performance

Avalanche trades-off better speeds and less server load for more processing power at each node

File Size (MB) Blocks Time

10 100 5 sec

50 100 37 sec

100 100 2m 21 sec

200 100 3m 38 sec

Note: Pentium III, 650MHz, 512MB RAM.

Decoding time is less than 4% of the total download

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Summary

•Adding resources in an arbitrary fashion is not efficient or cost effective

•We are witnessing a new Revolution •Peer-Assisted solutions can be used by content providers to provide hugely scalable, and very fast distribution of legal content at low cost