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1/30/2002Collaborative Computing in Higher Education1 Design Choices in P2P Infrastructure Wes Felter IBM Austin Research Lab

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Presentation on theme: "1/30/2002Collaborative Computing in Higher Education1 Design Choices in P2P Infrastructure Wes Felter IBM Austin Research Lab"— Presentation transcript:

1 1/30/2002Collaborative Computing in Higher Education1 Design Choices in P2P Infrastructure Wes Felter IBM Austin Research Lab wmf@austin.ibm.com

2 1/30/2002Collaborative Computing in Higher Education2 P2P Infrastructure Choices common to many P2P systems –Locations vs. Names –Network vs. App-Level Routing –RPC vs. Asynchronous Messaging –Lookup –Specialization –Incentives Common Ground?

3 1/30/2002Collaborative Computing in Higher Education3 Locations vs. Names Applies to peers, data, services Locations = URLs, Names = URNs Locations are simpler, faster, but inhibit replication –Used by Napster, Gnutella Names require directory service and namespace management –Used by Freenet, Mojo Nation, OceanStore

4 1/30/2002Collaborative Computing in Higher Education4 Network vs. App-level routing Network routing is “free”, minimizes latency –Used by Napster, Mojo Nation App-level routing can optimize for different metrics (e.g. privacy), provide multicast and replication –Used by Freenet, OceanStore Hybrids can work –Gnutella routes queries, but sends data direct

5 1/30/2002Collaborative Computing in Higher Education5 Network Routing

6 1/30/2002Collaborative Computing in Higher Education6 Application-Level Routing

7 1/30/2002Collaborative Computing in Higher Education7 Application-Level Routing 2

8 1/30/2002Collaborative Computing in Higher Education8 RPC vs. Async Messaging RPC has easy programming model, but: –Usually requires threads –Can encourage ignoring failures Asynchronous messaging –A different programming model (maybe) –Use event loops instead of threads –Design protocols as state machines

9 1/30/2002Collaborative Computing in Higher Education9 The Lookup Problem Map keys to values Minimize memory/storage use Minimize network round trips Be reliable (despite unreliable peers) Have an infinite “horizon” Resist attacks

10 1/30/2002Collaborative Computing in Higher Education10 Specialization All peers can perform exactly the same services –Freenet Or peers can specialize –Simple case: Sharing or not –More sophisticated: Gnutella Reflector, Mojo Nation index “trackers” –Some systems automatically elect “super-peers” based on their resources

11 1/30/2002Collaborative Computing in Higher Education11 An Unsolved Problem: Incentives Many P2P systems ask users to provide resources Why should they? Freeloading  Tragedy of the commons Don’t prohibit what you can’t prevent Reputations? Money? Real or Play?

12 1/30/2002Collaborative Computing in Higher Education12 Is there a common ground? Naming –SHA-1 is already popular Messaging –HTTP and XML protocols (XML-RPC, SOAP) –Sun’s JXTA is trying, with little adoption Directories

13 1/30/2002Collaborative Computing in Higher Education13 Moving Up a Level We know the primitives Are architectural models useful? –Data-oriented –Event-oriented –?

14 1/30/2002Collaborative Computing in Higher Education14 The End Wes Felter wmf@austin.ibm.com


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