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POND: THE OCEANSTORE PROTOTYPE

POND: THE OCEANSTORE PROTOTYPE. S. Rea, P. Eaton, D. Geels, H. Weatherspoon, J. Kubiatowicz U. C. Berkeley. Key Ideas. Versioning file system Location independent routing Uses hashes instead of addresses Mapping is done through Tapestry Byzantine update commitment

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POND: THE OCEANSTORE PROTOTYPE

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  1. POND:THE OCEANSTORE PROTOTYPE S. Rea, P. Eaton, D. Geels, H. Weatherspoon, J. Kubiatowicz U. C. Berkeley

  2. Key Ideas • Versioning file system • Location independent routing • Uses hashes instead of addresses • Mapping is done through Tapestry • Byzantine update commitment • By nodes holding primary copies (inner ring) • Proactive threshold signatures allow inner ring membership updates

  3. Key Ideas • Push-based update of other copies • Through an overlay multicast network • Copies are not permanent • Continuous archiving in erasure-coded form • Very reliable • Very slow access

  4. Motivation • Find a better solution forlong-term management of data • Enabling trends: • Near universal connectivity through high-bandwidth links • Very fast increase of disk storage capacity per unit cost

  5. OceanStore • Internet-scale cooperative file system • Will provide • High durability • Universal accessibility • Will use a two-tiered storage system • Stores data objects

  6. Two-tiered organization • Upper tier • Powerful , well connected hosts • Serialize changes and archive results • Lower tier • Less powerful hosts • Can be user workstations • Provide storage resources

  7. Two-tiered organization Archive Primary replica (in inner ring) Secondary replica Secondary replica Secondary replica

  8. Basic requirements • OceanStore should • Let information be accessed fromany location • Balance the tension between privacy and information sharing • Offer an easily understandable and usable model of data consistency • Guarantee data integrity

  9. First basic assumption • Infrastructure cannot be trusted , except in aggregate • Host and routers can fail arbitrarily • Must consider • Passive failures: host snooping, … • Active failures: host injecting malicious messages, …

  10. Second basic assumption • Infrastructure is continuously changing • Performance of communication paths varies • Resources enter and leave the network without warning • System should • Be self-organizing andself-repairing • Aim to be self-tuning

  11. The challenge • Build a system that provides • An expressive user interface • High data availability • High data durability • High data privacy and integrity atop an untrusted and ever changing base More ambitious than FARSITE

  12. The data model • OceanStore data object • Similar to a traditional file • Ordered sequence of read-only versions • Versioning • Simplifies consistency issues • Allows recovery of previous versions • Identical blocks are shared among versions

  13. Data object implementation (I) • Each data object has an AGUID(Active Globally-Unique Identifier) • Secure hash of application-level name and private key of owner • Each version has a VGUID (Version GUID) • BGUID of root block of a version • Each block has a BGUID (Block GUID) • Secure hash of block contents

  14. M M A data object AGUID VGUIDi VGUIDi+1 root block COW Indirect blocks COW Data blocks

  15. Data object implementation • AGUID, VGUID and BGUID arelocation-transparent • OceanStore relies on a lower-level serviceto map GIDs into addresses

  16. Application-level consistency (I) • Updating an object means creating a new version • Updates are • Atomic • Represented as an array of potential actions each guarded by a predicate

  17. Application-level consistency (II) • Actions can be • Appending data • Replacing bytes at a specific address • Predicates can be • Checking the latest version number of the object • Verifying values of bytes at a specific address

  18. Application-level consistency (II) • Actions can be • Appending data • Replacing bytes at a specific address • Predicates can be • Checking the latest version number of the object • Verifying values of bytes at a specific address

  19. Application-level consistency (III) • Predicate and action model • Allows to implement multiple level of consistency • Atomic transactions satisfying ACID properties for database applications • Weaker consistency for mailboxes

  20. A footnote • ACID properties of atomic transactions mean that atomic transactions • Are Atomic • Bring the database from one consistent state to another consistent state • Isolate their partial results until the transaction is completed • Guarantee the durability of final result

  21. Virtualization through Tapestry • OceanStore messages are addressed with a GUID • Tapestry forwards these messages to host containing a resource with that GUID • Fully decentralized service • Hosts can • Join tapestry by supplying its GUID • Publish the GUIDs of the resources they have

  22. Replication and consistency (I) • Each object has a single primary replica • Primary replica • Serializes and applies all updates • Creates a certificate (heartbeat ) mapping AGUID of object to GUID of its latest version • Controls access to the object • …

  23. Replication and consistency (II) • Heartbeat contains • An AGUID • A VGUID • A timestamp • A version sequence number • Getting the most recent version of object means getting its most recent heartbeat

  24. The inner ring • Small set of co-operating servers that manage primary replicas • Implement a Byzantine fault-tolerant protocol to • Agree on all updates to an object • Digitally sign the result

  25. Archival storage • Stores object versions that are not frequently accessed • Uses erasure codes • Each block • Partitioned into m fragments • Encoded into n > m fragments • Any subset of m fragments suffices to reconstitute the block

  26. Caching of data objects • Retrieving data from archive is slow • OceanStore also maintains of whole blocks • Secondary replicas • Heartbeats always come from theprimary replica • Updates of secondary replicas are done through a dissemination tree

  27. Path of an OceanStore update Archive Primary replica in inner ring Application Secondary replica Secondary replica Secondary replica

  28. Updating primary replicas (I) • Use a Byzantine fault-tolerant protocol • Tolerates up to f failures in a system made up of 3f + 1 hosts • Protocol uses digitally signed messages using symmetric key message authentication code • Faster than using public keys • Complicates the Byzantine agreement protocol

  29. Updating primary replicas (II) • Solution was to use • Symmetric keys for all communications within the inner ring • Public keys to communicate with all other machines

  30. Proactive threshold signatures • (listen to lecture)

  31. Tapestry Network (Java NBIO) Prototype software architecture Disseminationtree/replicas Inner ring Clientinterface Byzantineagreement Application Archive

  32. The prototype • Written in Java

  33. Conclusion

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