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Tapestry on PlanetLab Deployment Experiences and Applications Ben Zhao, Ling Huang, Anthony Joseph, John Kubiatowicz.

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Presentation on theme: "Tapestry on PlanetLab Deployment Experiences and Applications Ben Zhao, Ling Huang, Anthony Joseph, John Kubiatowicz."— Presentation transcript:

1 Tapestry on PlanetLab Deployment Experiences and Applications Ben Zhao, Ling Huang, Anthony Joseph, John Kubiatowicz

2 PlanetLab Meeting, December 2002ravenben@eecs.berkeley.edu Our Experience  Tapestry on PlanetLab  Deployed Java implementation on 67 nodes  Large scale routing and location measurements  6-7 node instances per physical node  A wish list  Uniformity in network configuration  Isolation (bounded scheduling latencies)  Dynamically updated pair-wise distance map  Transparent file synchronization

3 PlanetLab Meeting, December 2002ravenben@eecs.berkeley.edu Our Goals  A persistent Tapestry on PlanetLab  Application platform with extensible P2P routing  Persistent on selection of distributed PlanetLab nodes  Global backbone for larger Tapestry  Dynamic integration via introduction service  Incremental upgrades via ordered node restarts  Practical utility services available to PL users  Application / service control via IM (Shuttle)  Quick and dirty file sharing (Interweave)  Distributed file system (OceanStore)

4 PlanetLab Meeting, December 2002ravenben@eecs.berkeley.edu Snapshot Measurements  Real Tapestry network of 400+ nodes  Measured routing and location RDP under load  Scheduling / contention artificially increases RDP  Routing RDP median: 2.5  1  Location RDP median: 5  1

5 PlanetLab Meeting, December 2002ravenben@eecs.berkeley.edu Infrastructure Services  Simple but useful utility applications  Shuttle: decentralized chat service  Persistent state replicated across network  Decentralized message routing via Tapestry  Graphical UI, w/ AIM-like functionality  command mode can be used as a wall / zephyr – like tool  Interweave: deterministic file sharing  Simple file sharing via object location  Metadata replicas distributed across network  Search (match) on primary fields, pruning via secondary fields  Locates nearby object replicas


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