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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)
GET /index.html HTTP/1.0 HTTP/1.1 200 OK ... Client/Server Architecture Client Server
Disadvantages of C/S Architecture • Single point of failure • Strong expensive server • Dedicated maintenance (a sysadmin) • Not scalable - more users, more servers
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
Evolution at the Client Side IBM PC @ 4.77MHz 360k diskettes PC @ 4-core 4GHz 300GB HD DEC’S VT100 No storage 2008 ‘70 ‘80
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?
Resources Sharing • What can we share? • Computer resources • Shareable computer resources: • CPU cycles- seti@home, GIMPS • Bandwidth- PPLive, PPStream • Storage Space- OceanStore, Murex • Data - Napster, Gnutella
SETI@Home • 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
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?
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
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
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
MUREX: A Mutable Replica Control Scheme for Peer-to-Peer Storage Systems
HotOS Attendee Murex: Basic Concept
Video stream … … Peer-to-Peer Video Streaming
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
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 vs. 16 months, 23M Napster-style names are registered at Napster
“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 s o n g 5 4. Napster displays matches to beastieboy 5. beastieboy makes direct connection to kingrook for file transfer • song5.mp3
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.
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 = GNU Nutella Nutella: a hazelnut chocolate spread produced by the Italian confectioner Ferrero….
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
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
Peer-to-Peer Overlay Network Focus at the application layer
Peer-to-Peer Overlay Network End systems one hop (end-to-end comm.) a TCP thru the Internet Internet
Gnutella Protocol Scenario: Joining Gnutella Network • The new node connects to a well known ‘Anchor’ node or ‘Bootstrap’ node. • Then sends a PING message to discover other nodes. • PONG messages are sent in reply from hosts offering new connections with the new node. • Direct connections are then made to the newly discovered nodes. Gnutella Network New PING PING PING PONG PING PING A PING PING PONG PING PING PING
Gnutella: Issue a Request xyz.mp3 ?
Gnutella: Reply with the File Fully distributed storage and directory! xyz.mp3
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)
We Want • Efficiency : O(log(n)) messages per lookup • Scalability : O(log(n)) state per node • Robustness : surviving massive failures
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!
Object ID (key):AABBCC Object ID (key):DE11AC SHA-1 SHA-1 Example of Hasing Shark 194.90.1.5:8080
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
Mapping an object to the closest node with a larger key 0 M - a node - an data object
Internet Viewed as a Distributed Hash Table 0 2128-1 Hash table Peer node
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 node’s hash key. Objects’ directories are placed in (managed by) the node with the closest key • It must be adaptive to dynamic node joining and leaving
How to Find an Object? 0 2128-1 Hash table Peer node
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 i i+22 i+24 i+28 0 2128-1 Hash table Peer node
Chord Lookup – with finger table O(log n)hops (messages)for each lookup!! 1 I’m node 2. Please find key 14! 15 14 2 14 ∈[10,2) O(log n) states per node 3 12 Circular 4-bit ID space 10 14 ∈[14,2) 7
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