A%20Measurement%20Study%20of%20Peer-to-Peer%20File%20Sharing%20Systems%20by%20Stefan%20Saroiu%20P.%20Krishna%20Gummadi%20Steven%20D.%20Gribble

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A Measurement Study of Peer-to-Peer File
Sharing SystemsbyStefan SaroiuP. Krishna
GummadiSteven D. Gribble

• Presentation
• by
• Nanda Kishore Lella
• Lella.2_at_wright.edu

2
Outline

• P2P Overview
• What is a peer?
• Example applications
• Benefits of P2P
• P2P Content Sharing
• Challenges
• Group management/data placement approaches
• Measurement studies
• Conclusion

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What is Peer-to-Peer (P2P)?

• Most people think of P2P as music sharing
• Examples
• Napster
• Gnutella

4
What is a peer?

• Contrasted with Client-Server model
• Servers are centrally maintained and administered
• Client has fewer resources than a server

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What is a peer?

• A peers resources are similar to the resources
  of the other participants
• P2P peers communicating directly with other
  peers and sharing resources

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P2P Application Taxonomy
P2P Systems
Distributed Computing
File Sharing
Collaboration
Platforms JXTA
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P2P Goals/Benefits

• Cost sharing
• Resource aggregation
• Improved scalability/reliability
• Increased autonomy
• Anonymity/privacy
• Dynamism
• Ad-hoc communication

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P2P File Sharing

• Content exchange
• Gnutella
• File systems
• Oceanstore
• Filtering/mining
• Opencola

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Research Areas

• Peer discovery and group management
• Data location and placement
• Reliable and efficient file exchange
• Security/privacy/anonymity/trust

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Current Research

• Group management and data placement
• Chord, CAN, Tapestry, Pastry
• Anonymity
• Publius
• Performance studies
• Gnutella measurement study etc.

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Management/Placement Challenges

• Per-node state
• Bandwidth usage
• Search time
• Fault tolerance/resiliency

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Approaches

• Centralized
• Flooding
• Document Routing

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Centralized
Bob
Alice

• Napster model
• Benefits
• Efficient search
• Limited bandwidth usage
• Efficient network handling
• Drawbacks
• Central point of failure
• Limited scale

Jane
Judy
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Flooding
Carl
Jane

• Gnutella model
• Benefits
• No central point of failure
• Limited per-node state
• Drawbacks
• Slow searches
• Bandwidth intensive

Bob
Alice
Judy
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Document Routing
001
012

• FreeNet, Chord, CAN, Tapestry, Pastry model
• Benefits
• More efficient searching
• Limited per-node state
• Drawbacks
• Limited fault-tolerance vs redundancy

212 ?
212 ?
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212
305
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Document Routing CAN

• Associate to each node and item a unique id in an
  d-dimensional space
• Goals
• Scales to hundreds of thousands of nodes
• Handles rapid arrival and failure of nodes
• Properties
• Routing table size O(d)
• Guarantees that a file is found in at most dn1/d
  steps, where n is the total number of nodes

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CAN Example Two Dimensional Space

• Space divided between nodes
• All nodes cover the entire space
• Each node covers either a square or a rectangular
  area
• Example
• Node n1(1, 2) first node that joins ? cover the
  entire space

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n1
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CAN Example Two Dimensional Space

• Node n2(4, 2) joins ? space is divided between
  n1 and n2

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n1
n2
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CAN Example Two Dimensional Space

• Node n2(4, 2) joins ? space is divided between
  n1 and n2

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n2
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CAN Example Two Dimensional Space

• Nodes n4(5, 5) and n5(6,6) join

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n3
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n1
n2
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CAN Example Two Dimensional Space

• Nodes n1(1, 2) n2(4,2) n3(3, 5)
  n4(5,5)n5(6,6)
• Items f1(2,3) f2(5,1) f3(2,1) f4(7,5)

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n5
n4
n3
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CAN Example Two Dimensional Space

• Each item is stored by the node who owns its
  mapping in the space

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n4
n3
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f4
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n2
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CAN Query Example

• Each node knows its neighbors in the d-space
• Forward query to the neighbor that is closest to
  the query id
• Can route around some failures
• some failures require local flooding
• Example assume n1 queries f4

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n5
n4
n3
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f1
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CAN Query Example
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CAN Query Example
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CAN Query Example
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Node Failure Recovery

• Simple failures
• know your neighbors neighbors
• when a node fails, one of its neighbors takes
  over its zone
• More complex failure modes
• simultaneous failure of multiple adjacent nodes
• scoped flooding to discover neighbors
• hopefully, a rare event

Slide modified from another presentation
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Document Routing Chord

• MIT project
• Uni-dimensional ID space
• Keep track of log N nodes
• Search through log N nodes to find desired key

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Document Routing Chord(2)

• Each node and key is assigned an id.
• If a node needs a key,
• searches in its table of
• n nodes for the key.
• If fails, goes to the last node of its table and
  repeats until it finds the key.
• Search through log N nodes to find desired key

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Doc Routing Tapestry/Pastry

• Global mesh of meshes
• Suffix-based routing
• Uses underlying network distance in constructing
  mesh

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Naming in Tapestry

• Every node has a 4 bit
• name similar to IP address
• Each bit in the name
• can hold 16 types
• Keys present at the node are in accordance with
• the node name.

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Tapestry Routing
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Remaining Problems?

• Hard to handle highly dynamic environments
• Methods dont consider peer characteristics

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Measurement Studies

• Gnutella vs. Napster

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napster.com
P
P
D
S
S
Q
P
P
P
P
R
S
S
P
Q
P
P
P
Q
D
P
P
Q
Napster
Gnutella
Q
peer
query
P
D
file download
R
response
server
S
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Methodology

• 2 stages
• periodically crawl Gnutella/Napster
• discover peers and their metadata
• feed output from crawl into measurement tools
• bottleneck bandwidth SProbe
• latency SProbe
• peer availability LF
• degree of content sharing Napster crawler

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Crawling

• May 2001
• Napster crawl
• query index server and keep track of results
• query about returned peers
• dont capture users sharing unpopular content
• Gnutella crawl
• send out ping messages with large TTL

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Measurement Study

• How many peers are server-likeclient-like?
• Bandwidth, latency
• Connectivity
• Who is sharing what?

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Graph results

• CDF cumulative distribution function
• From this graph, we see that while 78 of the
  participating peers have downstream bottleneck
• bandwidths of at least 1000Kbps
• Only 8 of the peers have upstream bottleneck
  bandwidths of at least 10Mbps.
• 22 of the participating peers have upstream
  bottleneck bandwidths of 100Kbps or less.

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Reported Bandwidth
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Graph results

• The percentage of Napster users connected with
  modems (of 64Kbps or less) is
• About 25, while the percentage of Gnutella users
  with similar connectivity is as low as 8.
• 50 of the users in Napster and 60 of the users
  in Gnutella use broadband connections
• only about 20 of the users in Napster and 30 of
  the users in Gnutella have very high bandwidth
  connections
• Overall, Gnutella users on average tend to have
  higher
• downstream bottleneck bandwidths than
  Napster users.

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Graph results

• Approximately 20 of the peers have latencies of
  at least 280ms,
• Another 20 have latencies of at most 70ms

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Graph results

• This graph illustrates the presence of two
  clusters a smaller one situated at (20-60Kbps,
  100-1,000ms) and a larger one at over (1,000Kbps,
  60-300ms).
• horizontal lines in the graph they predicate that
  the latency also depends on the location of the
  peer for measuring system.

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Measured Uptime
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Number of Shared Files
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Correlation of Free-Riding with B/W
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Power law

• A connected cluster of peers that spans the
  entire network survives even in the presence of a
  large percentage p of random peer breakdowns,
  where p can be as large as

where m is the minimum node degree and K is the
maximum node degree. a lt3.
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Gnutella

• Popular sites
• 212.239.171.174
• adams-00-305a.Stanford.EDU
• 0.0.0.0

Fri Feb 16 052152-052322 PST
1771 hosts
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30 random failures
1771 471 294 hosts
Fri Feb 16 052152-052322 PST
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4 orchestrated failures
Fri Feb 16 052152-052322 PST
1771 - 63 hosts
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Results Overview

• Lots of heterogeneity between peers
• Systems should consider peer capabilities
• Peers lie
• Systems must be able to verify reported peer
  capabilities or measure true capabilities

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Points of Discussion

• Is it all hype?
• Should P2P be a research area?
• Do P2P applications/systems have common research
  questions?
• What are the killer apps for P2P systems?

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Conclusion

• P2P is an interesting and useful model
• There are lots of technical challenges to be
  solved