1. OceanStore: An Architecture for Global-Scale Persistent Storage
Authors: J. Kubiatowicz, D. Bindel, Y. Chen, S. Czerwinski, P. Eaton, D. Geels, R. Gummadi, S. Rhea, H. Weatherspoon, W. Weimer, C. Wells, and B. Zhao
University of California, Berkeley

2. Presentation Overview
Purpose and Vision of OceanStore
Data Location and Routing
Deep Archival Storage
Current Status

3. Applications for Persistent Storage
Storage for ubiquitous computing
Need for transparency
Large inexpensive memory allows for this
Personal Information Management tools:
Calendars, Contact Lists, etc.
Need consistency
Need privacy and security
Repositories, Digital Libraries

4. OceanStore Goals
OceanStore will accommodate persistent storage for ubiquitous computing.
Consistant
Highly Available
Durable Information
Divorced from location
Unique Goals
Levels of trusted and untrusted servers
Nomadic Data

5. Data Location and Routing
Routing is maintained as location independent by addressing GUIDs
Distributed data structure tracks the location of objects based on a Randomized Hierarchical Distributed Data Structure (Plaxton et al)
Routing is tiered
Local routing is probabilistic.
Backup is a highly redundant randomized hierarchical distributed data structure

6. Probabilistic Routing
Attenuated Bloom Filters
Multiple Hashes on the same data
Can give a false positive answer
Hash1(x) = 0
Hash2(x) = 3
Hash3(x) = 4 1
Hash1(x) = 2
GUID 4356
GUID 7382

7. Attenuated Bloom Filters
Union of neighbor-node filters yield a consistent hash.
Cheap and easy
Probabilistic

8. Wide-Scale Data Location
Bits in an object’s GUID becomes node IDs in a random hierarchical tree
Each link in the tree is graded by how much of the node ID’s match
L1 = No Match
L2 = LSB Match
Every level on a node has 16 links to closest ping IP’s.

9. Random Trees Roots occur where highest level links occur
By traversing through greater than or equal to links that have the desired bit strings the desired node ID is found.
Only disjoint networks prevent object location

10. Example

11. Deep Archival Storage Assumed uncorrelated faults
Highly redundant fragments
Intelligently distributed to both trusted and untrusted systems

12. Erasure Codes Reed-Solomon Codes
Transforms n fragments into 2n or 4n fragments
Any set of n fragments from the larger set of fragments can help determine the data carried by the original n fragments. B1 B2 B3 B4 P1 P2 P3 P4
Expensive
Code
Calculations
Using Erasure Codes

13. Smaller Example
Using Erasure Codes are similar to using parity bits in strings of bits.
b0 b1 b2 b3 p
1 ?
b0 b1 b2 b3 p =4
%2=0 =3
%2=1

14. Current State Pond: a prototype system Tapestry
Infrastructure for fault resilient, decentralized location and routing
Fast becoming a reality

15. Questions Comments