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

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P2P Networking

What is peer to peer p2p l.jpg

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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GET /index.html HTTP/1.0

HTTP/1.1 200 OK ...

Client/Server Architecture



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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

  • Today’s clients can perform more roles than just forwarding users requests

  • Today’s clients have:

    • more computing power

    • more storage space

  • Thin client  Fat client

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Evolution at the Client Side


@ 4.77MHz

360k diskettes

A PC @ 4GHz

100GB HD


No storage




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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@home, GIMPS

    • Data- Napster, Gnutella

    • Bandwidth- PPLive, PPStream

    • Storage Space- OceanStore, CFS, PAST

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  • SETI – Search for Extra-Terrestrial Intelligence

  • @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@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@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@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@Home - Example

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SETI@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 we’re 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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Video stream

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)

1984~2000, 23M domain names are counted


16 months, 23M Napster-style names are registered at Napster

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  • “beastieboy”

  • song1.mp3

  • song2.mp3

  • song3.mp3

  • “kingrook”

  • song4.mp3

  • song5.mp3

  • song6.mp3

  • “slashdot”

  • song5.mp3

  • song6.mp3

  • song7.mp3

Napster Sharing Style: hybrid center+edge

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






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

GNU’s Not Unix ….


Gnutella =



Nutella: a hazelnut chocolate spread produced by the Italian confectioner Ferrero….

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  • 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


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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!


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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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Object ID (key):AABBCC

Object ID (key):DE11AC



Example of Hasing


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Basic Idea

P2P Network

Publish (H(y))

Join (H(x))

Object “y”

Peer “x”



Peer nodes also have hash keys in the same hash space

Objects have hash keys



Hash key

Place object to the peer with closest hash keys

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Mapping Keys to Nodes



- a node

- an data object

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Viewed as a Distributed Hash Table







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  • 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 node’s 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?







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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(p+2i-1), i=1,..,m











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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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What’s next in the future?

  • P2P NEVs (Networked Virtual Environments)

    • P2P MMOGs (Massively Multiplayer Online Games)

    • P2P 3D Scene Streaming

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P2P-NVE:Peer-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: America’s 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 100,000concurrent 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 user’s 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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  • Used for physics, AI, agent behavior, some graphics, networking

  • Still on Moore’s 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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  • 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

★: self

▲: neighbors

Area of Interest(AOI)

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




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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)Acceptorsends back its own neighbor list

joining node connects with other nodes on the list

Joining node

Acceptor’s region

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Procedure (MOVE)

1)Positions sent to all neighbors, mark messages to B.N.

B.N. checks for overlaps between mover’s 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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