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UNIVERSITEITGENT

Peer-to-peer Networks :promise and trouble.

Bart DhoedtGhent University - Faculty of Applied SciencesDepartment of Information Technology (INTEC)

Presentation at NORDUnet Network ConferenceAugust 24-27, Reykjavik, 2003Tuesday, August 27, 2003.

e-mail : bart.dhoedt@intec.ugent.bephone : ++32 9 264 99 66

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OUTLINE

1. Introduction

2. Taxonomy of P2P-systems

3. Issues in P2P-systems

4. P2P-trends

5. Concluding remarks

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Defining P2P

• about sharing

• symmetric (architectural view)• creating an application-level overlay network• decentralized• application critical infrastructure owned by many

Ha

rdw

are

res

ou

rce s

So

ftw

are

res

ou

rces

disk space

bandwidth1001010

content

liability

computer cycles

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Sharing resources ? - estimate of edge resources

- available for P2P-network

total number of Internet hosts : 150 Maverage disk capacity : 10 GBaverage available memory : 128 MBaverage processing power : 1 GFLOPSaverage BW : 100Kb/s

1% hosts50% processing power50% memory10% disk space 25% network bandwidth 1.5 Mprocessors

disk storage : 1.5 PBprocessing power : 1.5 PFLOPSBW/link : 25 Kb/s

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Sharing resources ?

• What about supercomputers ?

12.3 TFLOPS8192 processors512 RS/6000 processing nodes6.2 TB memory storage160 TB disk storage110 M$106 tons

IBM ASCI White

1.5 PFLOPS1.5 M processors92 TB memory storage 1.5 PB disk storage? M$? tons

P2P-supercomputer

> x 10 !

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P2P @ edge ?

• How to unleash the power of the “Internet’s dark matter ?”

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[www.download.com]

P2P popularity

2003 summer download hit parade

1. Kazaa Media Desktop 2 644 777 261 405 2952. ICQ Lite 588 141 25 423 0643. AOL Instant Messenger (AIM) 532 897 17 521 1904. iMesh 392 703 55 145 2695. WinZip 351 865 100 741 7906. ICQ Pro 2003a beta 332 624 233 204 7127. Spybot – Search & Destroy 232 993 2 764 3808. Ad-aware 224 720 19 078 5559. Morpheus 179 347 114 140 26210. DownloadAccelerator Plus 119 601 36 355 895

P2PP2PP2PP2P

P2P

[Last week] [Total]

P2P

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P2P popularity

Internet Applications Adoption Rate

0

10

20

30

40

50

60

70

1 3 5 7 9

11

13

15

17

19

21

23

Month

Millions

Hotmail ICQ Napster

Gnutella network : up to 400 000 nodes operating world wide

Napster : the early days …

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Architectural view

Mediated P2P Pure P2P Hybrid P2P

NapsterAudiogalaxy

Early GnutellaFreeNet

GnutellaFastTrackKazaa

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P2P-architectures

mediated pure hybrid

data traffic P2P P2P P2P

control traffic client-server P2P local : client-serverlong distance : P2P

efficiency + efficient search+ efficient control

- inefficient search- BW consuming +/-

scalability - control hot spot(mirrors needed ?)

- BW needed grows rapidly

good compromise

robustness - single point of failure- easy to attack

+ graceful degradation+ difficult to attack

?

accountability easy difficult difficult

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P2P taxonomy

content sharing

distributed computing

instant messaging

collaborative working

mediated pure hybrid

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File Sharing performance

150 M searches/day1.6 M downloads/day

10 TB data transfer/day 1-2 TB data transfer/day

100 servers 15000 servers

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Distributed computing performance

10 tapes/week, 350 GB

10 000 0.3 MB work units

35 GB/tape16 hours recorded data

SETI=“Search for extraterrestrial Intelligence”

• started in 1998 as a 2 year project (but still running)• 4 M users signed up so far• Radio telescope data sent to clients for digital signal analysis• Nodes process data when cycles are available

(works as screen saver)• Using resources to allow better signal analysis

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Distributed computing performance

computations per work unit 3.1x1012 FP-operationswork unit throughput 700 000/day

22x1017 FLOP/day

>25 TFLOPS

ASCI White@DoESETI@home

Processing 25 TFLOPS 12.3 TFLOPS

Cost 1 M USD 110 M USD

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Scaling problems

Mechanisms in GNUTELLA to limit traffic• Network horizon set by TTL • Descriptor ID’s avoid cyclic routing• PONG/QueryHIT/Push NOT flooded

BUT ...

Bandwidth

0

2000

4000

6000

8000

10000

0 2 4 6 8

Horizon

KB

/PIN

G

“1 Gnutella request would cause 90MB data traffic on

Napster scale network”

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Scaling answers1. Reduce network horizon to reduce f2. Use of reflectors

= node with high BW available- mimics peer sharing all files of its “clients”

3. Use of UltraPeers= same principle as reflector, but chosen dynamically

low access BW

high BW access

handles allPING/PONG

QUERY/QUERYHITTraffic

handle ONLY download traffic

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Robustness• self-organization leads to power-law networks

(1% of servents shows server-like behaviour …)• very robust to random node failure• more vulnerable to targeted attacks

Simulation result for FreeNet peers

[T. Hong, “Performance”, Chapter 14 in “Peer-to-peer : Harnessing theBenefits of a Disruptive Technology”, ISBN 0-596-00110-X, O’Reilly,March 2001.]

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Free-riding on Gnutella

Network size since Jan 2002

- only 30 % of nodes offering content- 50% of queries satisfied by 1% of servents

[www.limewire.com]

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Overlay mismatch

Mismatch between application layernetwork and physical network

• 40% Gnutella clients belong to top 10% AS• only 2-5% links within AS

based on domain names

based on network traffic analysis

Gnutella’s clustering logic shows no/little correlation with domain name based clustering

[M. Ripeanu, A. Iamnichi, I. Foster, “Mapping the Gnutella Network”, IEEE Internet Computing, January-February 2002.]

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Business Models

How to monetise P2P ?

• authors agree on “P2P business models are unclear”• reality : few companies make money on P2P• current situation : File sharing application sponsored by advertisement (banners)• some other possibilities

• micropayment mechanisms• indirect mechanisms

(P2P will increase BW-need and hence …) • tip based strategy (cf. US-model …)• make “low”-quality content available to get people interested in specific content• make use of end users devices to reduce cost !

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Problems/issues/barriers/challenges

Problems Solutions

node/link transient naturerobustness

scalabilitybandwidth consumption

Network discontinuities(firewalls, (dynamic) NAT)

File-sharing : content redundancyCycle-sharing : checkpointing

Hybrid approachAvoid floodings (e.g. FreeNet : intelligent routing)Content/Query cachingTTLAvoid routing cycles

(Ab)use of port 80Rendez-vous servers

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Problems/issues/barriers/challenges

Problems Solutions

application redesign

free-ridingaccountability

asymmetric bandwidth in access (ADSL, HFC)

inefficient overlay

P2P-frameworks

micro-payment

combine uplink capacity(e-donkey)

Network/infrastructureaware routing

Privacy/trustAnonymity

Encryption techniques(e.g. FreeNet : plausible deniability for node operators)

business models ? ???

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P2P-trends

• emergence of platforms

• convergence between Grid-computing and P2P-technology

• enhance P2P-performance • semantic searches

(Tapestry, Content Addressable Networks …)• Query/result caching

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Platform emergence

File sharing

Application areas

Distributedcomputing

InstantMessaging

Collaboration

• for 1 application area• non-generic

• 1 application class• 1 specific problem

• network interoperability ?

FreenetGnutella

GrooveSETI@home

eDonkey

• offer generic services• support the P2P paradigm• used to build P2P applications

? ?

? ??

?

DedicatedApplication Programs

and Protocols

PlatformsFrameworks

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JXTA

• developed by Sun Microsystems• set of 6 XML based open protocols• Java API offered

Applications

Services

Core

Security

Peer Groups Peer Pipes Peer Monitoring

JXTA Community Services

Sun JXTAServices

PeerCommands

JXTAShell

Sun JXTAApplications

JXTA CommunityApplications

peer establishmentcommunication managementrouting

indexingsearchingfile sharing

e-mailauctioningdata storage

[http://www.jxta.org]

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BOINC

• Berkeley Open Infrastructure for Network Computing • allows participants to participate to solve selected problems• = “generic SETI@Home”

[http://boinc.berkeley.edu]

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Conclusions

For network operators

P2P applications can be very BW-consuming• extremely popular (and addictive)• use of inefficient strategies (broadcast, flooding, …)• “tragedy of the commons”

Danger for Bottlenecks • overlay network has little relation to physical infrastructure• symmetric relations between peers

Change in user behaviour • “always” online• information provider AND information consumer

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Conclusions

For application developers

People are willing to share resources for free(and even want to spend money …)• make people feel they participate in a large project• give some credit to users (competition) (top 10 list, eternal fame if solution is found, …)

To avoid digging ones own grave • avoid BW-consuming strategies• include micropayment/trust mechanisms as

- encouragement to participate- avoid free-riding- avoid DoS attacks

People are (extremely) interested in digital content

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Conclusions

For application developers

Hacker danger • need for encryption mechanisms

High performance P2P-platforms are emergent

• reuse of efforts• reuse of user community

Make sure your application has some scaling effect • the more users, the more interesting to join !