Peertopeer Networks : promise and trouble.

1
Peer-to-peer Networks promise and trouble.
Bart Dhoedt Ghent University - Faculty of Applied
Sciences Department of Information Technology
(INTEC)
e-mail bart.dhoedt_at_intec.ugent.be phone 32
9 264 99 66
Presentation at NORDUnet Network
Conference August 24-27, Reykjavik, 2003 Tuesday,
August 27, 2003.
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OUTLINE

• 1. Introduction
• 2. Taxonomy of P2P-systems
• 3. Issues in P2P-systems
• 4. P2P-trends
• 5. Concluding remarks

3
Defining P2P

• No agreement on formal definition
• (Possible) definition of a P2P-networks

A distributed network architecture may be called
a Peer-to-Peer (P-to-P, P2P, ) network, if the
participants share a part of their own hardware
resources (processing power, storage capacity,
network link capacity, printers, ). These shared
resources are necessary to provide the Service
and content offered by the network (e.g. file
sharing or shared workspaces for collaboration)
They are accessible by other peers directly,
without passing intermediary entities. The
participants of such a network are thus resource
(Service and content) providers as well as
resource (Service and content) requestors
(Servent-concept).
W. Kellerer, Dienstarchitekturen in der
Telekommunikation - Evolution, Methoden und
Vergleich, Technical Report TUM-LKN-TR-9801,1998.

1. Introduction
4
Defining P2P

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

P2P is
Software resources
Hardware resources
1. Introduction
5
Sharing resources ?

• estimate of edge resources
• - available for P2P-network

total number of Internet hosts 150 M average
disk capacity 10 GB average available memory
128 MB average processing power 1
GFLOPS average BW 100Kb/s
1 hosts 50 processing power 50 memory 10 disk
space 25 network bandwidth
1. Introduction
6
Sharing resources ?

• What about supercomputers ?

1. Introduction
7
P2P _at_ edge ?

• How to unleash the power of the Internets dark
  matter ?

1. Introduction
8
P2P popularity
2003 summer download hit parade
Total
Last week
P2P
1. Kazaa Media Desktop 2 644 777 261 405 295 2.
ICQ Lite 588 141 25 423 064 3. AOL
Instant Messenger (AIM) 532 897 17 521
190 4. iMesh 392 703 55 145 269 5.
WinZip 351 865 100 741 790 6. ICQ Pro
2003a beta 332 624 233 204 712 7. Spybot
Search Destroy 232 993 2 764 380 8.
Ad-aware 224 720 19 078 555 9.
Morpheus 179 347 114 140 262 10.
DownloadAccelerator Plus 119 601 36 355 895
P2P
P2P
P2P
P2P
P2P
www.download.com
1. Introduction
9
P2P popularity
Napster the early days
Gnutella network up to 400 000 nodes operating
world wide
1. Introduction
10
Architectural view
Mediated P2P
Pure P2P
Hybrid P2P
Early Gnutella FreeNet
Gnutella FastTrack Kazaa
Napster Audiogalaxy
2. Taxonomy
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P2P-architectures
mediated
pure
hybrid
P2P
P2P
P2P
data traffic
control traffic
local client-server long distance P2P
client-server
P2P
efficiency
efficient search efficient control
- inefficient search - BW consuming
/-
- control hot spot (mirrors needed ?)
- BW needed grows rapidly
good compromise
scalability
robustness
- single point of failure - easy to attack
graceful degradation difficult to attack
?
accountability
easy
difficult
difficult
2. Taxonomy
12
Application view

• According to application area

distributed computing
content sharing
instant messaging
collaborative working
2. Taxonomy
13
P2P taxonomy
content sharing
distributed computing
instant messaging
collaborative working
mediated
pure
hybrid
2. Taxonomy
14
File Sharing performance

150 M searches/day
1.6 M downloads/day
10 TB data transfer/day
1-2 TB data transfer/day
100 servers
15000 servers
2. Taxonomy
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Distributed computing performance

• 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

2. Taxonomy
16
Distributed computing performance
computations per work unit 3.1x1012
FP-operations work unit throughput 700 000/day
2. Taxonomy
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Scaling problems
Mechanisms in GNUTELLA to limit traffic

• Network horizon set by TTL
• Descriptor IDs avoid cyclic routing
• PONG/QueryHIT/Push NOT flooded

BUT ...
1 Gnutella request would cause 90MB data
traffic on Napster scale network
3. Issues
18
Scaling answers
1. Reduce network horizon to reduce f 2. 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
handles all PING/PONG QUERY/QUERYHIT Traffic
handle ONLY download traffic
3. Issues
19
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,
OReilly,March 2001.
3. Issues
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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
3. Issues
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Overlay mismatch
Mismatch between application layer network and
physical network
based on network traffic analysis

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

based on domain names
Gnutellas 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.
3. Issues
22
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 !

3. Issues
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Problems/issues/barriers/challenges
Problems
Solutions
node/link transient nature robustness
scalability bandwidth consumption
Network discontinuities (firewalls, (dynamic) NAT)
3. Issues
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Problems/issues/barriers/challenges
Solutions
Problems
Privacy/trust Anonymity
application redesign
free-riding accountability
asymmetric bandwidth in access (ADSL, HFC)
inefficient overlay
business models ?
3. Issues
25
P2P-trends

• emergence of platforms
• convergence between Grid-computing and
  P2P-technology
• enhance P2P-performance
• semantic searches (Tapestry, Content
  Addressable Networks )
• Query/result caching

4. Trends
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Platform emergence
Application areas
File sharing
Distributedcomputing
Instant Messaging
Collaboration
4. Trends
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JXTA

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

e-mail auctioning data storage
indexing searching file sharing
Sun JXTA Applications
JXTA Community Applications
Applications
JXTA Shell
Peer Commands
peer establishment communication
management routing
JXTA Community Services
Sun JXTA Services
Services
Peer Groups
Peer Pipes
Peer Monitoring
Core
Security
http//www.jxta.org
4. Trends
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BOINC

• Berkeley Open Infrastructure for Network
  Computing
• allows participants to participate to solve
  selected problems
• generic SETI_at_Home

http//boinc.berkeley.edu
4. Trends
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Conclusions
For network operators
5. Conclusions
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Conclusions
For application developers
5. Conclusions
31
Conclusions
For application developers
5. Conclusions