1. Colin J. MacDougall

2.  Class of Systems and Applications  “Employ distributed resources to perform a critical function in a decentralized manner”  Distributed Resources ◦ Computing power, storage, bandwidth, etc.  Critical Functions ◦ Distributed computing, data sharing, communication, etc.  Decentralization ◦ Algorithms, data, meta-data

4.  Pre 1980s ◦ Telephony – Communication between peers  1980s – Early 1990s ◦ FTP with Archie indexing  Mid 1990s ◦ Abandoned in favor of client-server  1999 ◦ Napster  2000s ◦ SETI@home, Gnutella, JXTA,.NET, Groove,...

5.  Cost Sharing and Reduction ◦ Server normally handles the brunt of costs ◦ Peers can share costs between them ◦ Ex. Napster shared storage space among peers  Resource Aggregation and Interoperability ◦ Huge amounts of storage, computation available ◦ Sum of peer’s resources is accessible ◦ Ex. SETI@home is faster than the fastest supercomputer in the world (as of 2003)

6.  Improved Scalability and Reliability ◦ P2P has no (or little) central authority ◦ Must be able to locate resources in a network of peers ◦ Must remain operative when peers disconnect or networks fail  Increased Autonomy ◦ Local nodes do work on behalf of their users ◦ Users have control over their data and work

7.  Anonymity ◦ Of Author, Publisher, Reader, Server, Document, Query ◦ Uses multicasting, covert paths, identity spoofing, non-voluntary placement, encryption, etc.  Dynamism ◦ Peers join and drop the network continuously ◦ Must be able to allocate work to new resources ◦ Must be able to recover from uncompleted work on dropped resources

8.  Distributed Computing ◦ Sharing a computation intensive task between peers ◦ Ex. SETI@home  File Sharing ◦ Storing information on and retrieving information from peers ◦ Ex. Napster, Gnutella  Communication & Collaboration ◦ User interaction without central server ◦ Ex. Instant Messaging  Platforms ◦ Contain some capacity for all of the above services ◦ Serve as an environment for P2P applications ◦ Ex. JXTA,.NET

9.  Divide problem into small, independent parts  Limited to embarrassingly parallel problems ◦ Cluster-like communication ruled out by network latency ◦ Single Process Multiple Data  Financial Applications ◦ Complex market simulations  Portfolio pricing, risk hedge calculation, credit evaluation, etc. ◦ Security concerns  Biotech Applications ◦ Genome@home, Folding@home

10.  Content storage and exchange  Circumvent bandwidth limitations  Technical Issues ◦ Network Consumption ◦ Security ◦ Search Capabilities

11.  Instant messaging, online games, shared applications  Generally event-driven  Technical Challenges ◦ Location of peers ◦ Fault Tolerance ◦ Realtime Constraints

12.  Execution environments providing layer between OS and applications  Support primary P2P components ◦ Naming, discovery, communication, security, aggregation

16.  D.S. Milojicic, V. Kalogeraki, R. Lukose, K. Nagaraja, J. Pruyne, B. Richard, S. Rollins, Z. Xu, Peer-to-peer computing, Technical Report HPL-2002-57R1, HP Laboratories, Palo Alto, USA, 3 July 2003