P2P Networking

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P2P Networking
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What is peer-to-peer (P2P)?

• Peer-to-peer is a way of structuring distributed
  applications such that the individual nodes have
  symmetric roles. Rather than being divided into
  clients and servers each with quite distinct
  roles, in P2P applications a node may act as both
  a client and a server.-- Charter of
  Peer-to-peer Research Group, IETF/IRTF, June 24,
  2004(http//www.irtf.org/charters/p2prg.html)

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Client/Server Architecture
Client
Server
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Disadvantages of C/S Architecture

• Single point of failure
• Strong expensive server
• Dedicated maintenance (a sysadmin)
• Not scalable - more users, more servers

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The Client Side

• Todays clients can perform more roles than just
  forwarding users requests
• Todays clients have
• more computing power
• more storage space
• Thin client ? Fat client

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Evolution at the Client Side
IBM PC _at_ 4.77MHz 360k diskettes
A PC _at_ 4GHz 100GB HD
DECS VT100 No storage
2007
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What Else Has Changed?

• The number of home PCs is increasing rapidly
• Most of the PCs are fat clients
• As the Internet usage grow, more and more PCs are
  connecting to the global net
• Most of the time PCs are idle
• How can we use all this?

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Resources Sharing

• What can we share?
• Computer resources
• Shareable computer resources
• CPU cycles - seti_at_home, GIMPS
• Data - Napster, Gnutella
• Bandwidth - PPLive, PPStream
• Storage Space - OceanStore, CFS, PAST

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SETI_at_Home

• SETI Search for Extra-Terrestrial Intelligence
• _at_Home On your own computer
• A radio telescope in Puerto Rico scans the sky
  for radio signals
• Fills a DAT tape of 35GB in 15 hours
• That data have to be analyzed

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SETI_at_Home (cont.)

• The problem analyzing the data requires a huge
  amount of computation
• Even a supercomputer cannot finish the task on
  its own
• Accessing a supercomputer is expensive
• What can be done?

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SETI_at_Home (cont.)

• Can we use distributed computing?
• YEAH
• Fortunately, the problem can be solved in
  parallel - examples
• Analyzing different parts of the sky
• Analyzing different frequencies
• Analyzing different time slices

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SETI_at_Home (cont.)

• The data can be divided into small segments
• A PC is capable of analyzing a segment in a
  reasonable amount of time
• An enthusiastic UFO searcher will lend his spare
  CPU cycles for the computation
• When? Screensavers

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SETI_at_Home - Example
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SETI_at_Home - Summary

• SETI reverses the C/S model
• Clients can also provide services
• Servers can be weaker, used mainly for storage
• Distributed peers serving the center
• Not yet P2P but were close
• Outcome - great results
• Thousands of unused CPU hours tamed for the
  mission
• 3 millions of users

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Google -- Larry Page and Sergey Brin
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Cloud computing
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• MUREX A Mutable Replica Control Scheme for
  Peer-to-Peer Storage Systems

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Murex Basic Concept
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Peer-to-Peer Video Streaming
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Peer-to-Peer Video Streaming
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Napster -- Shawn Fanning
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History of Napster (1/2)

• 5/99 Shawn Fanning (freshman, Northeastern
  University) founds Napster Online (supported by
  Groove)
• 12/99 First lawsuit
• 3/00 25 Univ. of Wisconsin traffic on Napster

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History of Napster (2/2)

• 2000 estimated 23M users
• 7/01 simultaneous online users 160K
• 6/02 file bankrupt
• 10/03 Napster 2 (Supported by Roxio) (users
  should pay 9.99/month)

19842000, 23M domain names are counted vs. 16
months, 23M Napster-style names are registered at
Napster
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Napster Sharing Style hybrid centeredge
Title User Speed song1.mp3
beasiteboy DSL song2.mp3 beasiteboy
DSL song3.mp3 beasiteboy
DSL song4.mp3 kingrook T1 song5.mp3
kingrook T1 song5.mp3 slashdot
28.8 song6.mp3 kingrook
T1 song6.mp3 slashdot 28.8 song7.mp3
slashdot 28.8
1. Users launch Napster and connect to Napster
server
2. Napster creates dynamic directory from users
personal .mp3 libraries
3. beastieboy enters search criteria
s
o
n
g
5
4. Napster displays matches to beastieboy
5. beastieboy makes direct connection to kingrook
for file transfer

• song5.mp3

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Gnutella History

• Gnutella was written by Justin Frankel, the
  21-year-old founder of Nullsoft.
• (Nullsoft acquired by AOL, June 1999)
• Nullsoft (maker of WinAmp) posted Gnutella on the
  Web, March 14, 2000.
• A day later AOL yanked Gnutella, at the behest of
  Time Warner.
• Too late 23k users on Gnutella
• People had already downloaded and shared the
  program.
• Gnutella continues today, run by independent
  programmers.

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Gnutella -- Justin Frankel and Tom Pepper
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The Animal GNU Either of two large African
antelopes (Connochaetes gnou or C. taurinus)
having a drooping mane and beard, a long tufted
tail, and curved horns in both sexes. Also
called wildebeest.
GNU Recursive Acronym GNUs Not Unix .

Gnutella
GNU
Nutella
Nutella a hazelnut chocolate spread produced by
the Italian confectioner Ferrero .
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GNU

• GNU's Not Unix
• 1983 Richard Stallman (MIT) established Free
  Software Foundation and Proposed GNU Project
• Free software is not freeware
• Free software is open source software
• GPL GNU General Public License

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About Gnutella

• No centralized directory servers
• Pings the net to locate Gnutella friends
• File requests are broadcasted to friends
• Flooding, breadth-first search
• When provider located, file transferred via HTTP
• History
• 3/14/00 release by AOL, almost immediately
  withdrawn

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Peer-to-Peer Overlay Network
Focus at the application layer
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Peer-to-Peer Overlay Network
End systems
one hop (end-to-end comm.)
a TCP thru the Internet
Internet
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Topology of a Gnutella Network
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Gnutella Issue a Request
xyz.mp3 ?
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Gnutella Flood the Request
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Gnutella Reply with the File
Fully distributed storage and directory!
xyz.mp3
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So Far
n number of participating nodes

• Centralized
• - Directory size O(n)
• - Number of hops O(1)
• Flooded queries
• - Directory size O(1)
• - Number of hops O(n)

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We Want

• Efficiency O(log(n)) messages per lookup
• Scalability O(log(n)) state per node
• Robustness surviving massive failures

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How Can It Be Done?

• How do you search in O(log(n)) time?

• Binary search

• You need an ordered array
• How can you order nodes in a network and data
  objects?

• Hash function!

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Example of Hasing
Shark
194.90.1.58080
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Basic Idea
P2P Network
Publish (H(y))
Join (H(x))
Object y
Peer x
H(y)
H(x)
Peer nodes also have hash keys in the same hash
space
Objects have hash keys
y
x
Hash key
Place object to the peer with closest hash keys
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Mapping Keys to Nodes
0
M
- a node
- an data object
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Viewed as a Distributed Hash Table
0
2128-1
Hash table
Peer node
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DHT

• Distributed Hash Table
• Input key (file name)Output value
  (file location)
• Each node is responsible for a range of the hash
  table, according to the nodes hash key. Objects
  are placed in (managed by) the node with the
  closest key
• It must be adaptive to dynamic node joining and
  leaving

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How to Find an Object?
0
2128-1
Hash table
Peer node
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Simple Idea

• Track peers which allow us to move quickly across
  the hash space
• a peer p tracks those peers responsible for hash
  keys (p2i-1), i1,..,m

0
2128-1
i22
i24
i28
i
Hash table
Peer node
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DHT example Chord -- Ring Structure
N8 knows of only six other nodes.
Circular 6-bit ID space
O(log n) states per node
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DHT example Chord -- Ring Structure
O(log n)-hop query cost
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Classification of P2P systems

• Hybrid P2P Preserves some of the traditional
  C/S architecture. A central server links between
  clients, stores indices tables, etc
• Napster
• Unstructured P2P no control over topology and
  file placement
• Gnutella, Morpheus, Kazaa, etc
• Structured P2P topology is tightly controlled
  and placement of files are not random
• Chord, CAN, Pastry, Tornado, etc

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Whats next in the future?

• P2P NEVs (Networked Virtual Environments)
• P2P MMOGs (Massively Multiplayer Online Games)
• P2P 3D Scene Streaming

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P2P-NVEPeer-to-Peer Networked Virtual
Environment

• Part of the following slides are adapted from
  www.movesinstitute.org/mcgredo/NVE.ppt

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NVE Examples

• Commercial
• FPS Americas Army
• MMOGQuake, Unreal, EverQuest, World of Warcraft
  (WoW), Lineage, Second Life, FPS (first person
  shooter)
• Research NPSNET, Dive, MASSIVE
• Military Close Combat Tactical Trainer, SIMNET

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Americas Army
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Massively Multiplayer Online Games

• MMOGs are growing quickly
• 8 million registered users for World of Warcraft
• Over 100,000 concurrent players
• Billion-dollar business

Adaptive Computing and Networking Lab, CSIE, NCU
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Adaptive Computing and Networking Lab, CSIE, NCU
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Adaptive Computing and Networking Lab, CSIE, NCU
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Adaptive Computing and Networking Lab, CSIE, NCU
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Close Combat Tactical Trainer
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NVE (1)

• Networked Virtual Environments (NVEs) are
  computer-generated virtual world where multiple
  geographically distributed users can assume
  virtual representatives (or avatars) to
  concurrently interact with each other
• A.K.A. Distributed Virtual Environments (DVEs)

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NVE (3)

• 3D virtual world with
• People (avatar)
• Objects
• Terrain
• Agents
• Each avatar can do a lot of operations
• Move
• Chat
• Other actions

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NVE Components

• Graphic display
• User input and communication
• Processing/CPU
• Data network

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NVE Components Graphics

• The display and CPU have become astonishingly
  cheap in the last few years
• We typically need to draw in 3D on the display.
  The great thing about standards is that there are
  so many to choose from.
• OpenGL, X3D, Java3D
• Varying degrees of realism, with FPS emphasizing
  photorealism and others like EverQuest or Sims
  Online sacrificing graphics for better gameplay
  in other aspects

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NVE User Interfaces

• You can have all sorts of input/output devices at
  the users location.
• With commercial games it is often a display,
  keyboard, and mouse.
• Military simulations may have more elaborate user
  environments, such as a mockup of an M1 tank
  interior
• Some fancy UIs, such as head-mounted displays,
  caves, haptic feedback, data gloves, etc.

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Processing/CPU

• Used for physics, AI, agent behavior, some
  graphics, networking
• Still on Moores law curve. 4 GHz machines are
  cheap and plentiful.

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Data Network

• Networks are a real bottleneck in NVE design.
  Why?
• Players can send out position updates at 30/sec X
  50 bytes/update 42 bytes/packet overhead
  22,000 bits/sec/player
• Even a 1 mbit/sec connection can run out of
  bandwidth after 40-50 players

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Data Network

• Latency is another big implementation problem.
  The position updates that arrive at hosts are
  always out of date, so we only know where the
  object was in the past
• This may be a big problem (wide area network
  across a satellite link) or a small problem
  (everyone on a LAN)

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Issues for NVEs

• Scalability
• To accommodate as many as participants
• Consistency
• All participants have the same view of object
  states
• Persistency
• All contents (object states) in NVE need to exist
  persistently
• Reliability
• Need to tolerate H.W and S.W. failures
• Security
• To prevent cheating and to keep user information
  and game state confidentially.

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Architectures

• NVE architectures fall between two extreme poles
  peer-to-peer and client-server
• In a Client-Server architecture, a server is
  responsible for sending out updates to the other
  hosts in the NVE
• In a P2P architecture, all hosts communicate with
  other hosts

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Architectures (Client-Server)
Popular with commercial game engines
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Architectures (P2P)
More popular in research and military
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The Scalability Problem (1)

• Client-server has inherent resource limit

Resource limit
Adaptive Computing and Networking Lab, CSIE, NCU
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The Scalability Problem (2)

• Peer-to-Peer Use the clients resources

Resource limit
Adaptive Computing and Networking Lab, CSIE, NCU
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You only need to know some participants
Area of Interest(AOI)

• ? self
• ? neighbors

Adaptive Computing and Networking Lab, CSIE, NCU
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Voronoi-based Overlay Network VON

• Observation
• for virtual environment applications, the
  contents we want are messages from AOI neighbors
• Content discovery is a neighbor discovery problem
• Solve the Neighbor Discovery Problem in a
  fully-distributed, message-efficient manner.
• Specific goals
• Scalable ? Limit minimize message traffics
• Responsive ? Direct connection with AOI neighbors

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Voronoi Diagram

• 2D Plane partitioned into regions by sites, each
  region contains all the points closest to its site

Neighbors
Region
Site
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Design Concepts
Use Voronoi to solve the neighbor discovery
problem

• Each node constructs a Voronoi of its neighbors
• Identify enclosing and boundary neighbors
• Mutual collaboration in neighbor discovery

? node i and the big circle is its AOI
enclosing neighbors ? boundary neighbors ? both
enclosing and boundary neighbors ? normal AOI
neighbors ? irrelevant nodes
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Procedure (JOIN)

• 1) Joining node sends coordinates to any existing
  node
• Join request is forwarded to acceptor
• 2) Acceptor sends back its own neighbor list
• joining node connects with other nodes on the
  list

Joining node
Acceptors region
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Procedure (MOVE)

• 1) Positions sent to all neighbors, mark messages
  to B.N.
• B.N. checks for overlaps between movers AOI and
  its E.N.
• 2) Connect to new nodes upon notification by B.N.
  

Boundary neighbors
New neighbors
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Procedure (LEAVE)

• 1) Simply disconnect
• 2) Others then update their Voronoi
• new B.N. is discovered via existing B.N.

Leaving node (also a B.N.)
New boundary neighbor
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• QA