1. Depot: Cloud Storage with Minimal Trust OSDI 2010 Prince Mahajan, Srinath Setty, Sangmin Lee, Allen Clement, Lorenzo Alvisi, Mike Dahlin, and Michael Walfish The University of Texas at Austin Presented by: Masoud SAEIDA ARDEKANI 24/11/2011

2. Motivation Cloud services are: – Fault-prone – Black-box Clients – Hesitate to trust cloud services – Rely on end-to-end checks of properties

3. What is Depot? A cloud storage with minimal trust Eliminate trust for: – Put availability – Eventual consistency – Staleness-detection – Dependency preservation Minimizes trust for: – Get availability – Durability

4. Depot Overview Consistency Despite Faults! – Add metadata to Puts – Add local states to nodes – Add checks on received metadata Put (k, ) Get (k) {nodeID, key, H(value), localClock, History} nodeID Gossip N1 N2

5. Checks upon receiving an update Accept an update u sent by N if: – u must be properly signed – There is not omission All updates in u’s history are also in local history – History is not modified u is newer than any prior update by N

6. But, faults can cause forks! Forks: – Node’s local view is consistent! – Inconsistent views between different nodes! Prevent eventual consistency! N1N2F

7. Join forks for eventual consistency Faulty node  Two (correct) virtual node N1N2

8. Faults vs Concurrency Converting faults into concurrency – Allow correct nodes to converge Concurrency can introduce conflicts! – Already possible due to decentralized servers! – Applications for high availability allow concurrent writes Depot exposes the conflicts to the application – GET operation returns set of most recent concurrent updates

9. Consistency Causal Consistency (CC) – If update u 1 by a node depends on an update u 0 by any node, then u 0 becomes observable before u 1 at any node. Fork-Join Causal (FJC) Consistency – If update u 1 by a correct node depends on an update u 0 by any node, then u 0 becomes observable before u 1 at any correct node.

10. Ensuring Properties Safety (FJC consistency) – Local checks Liveness – Reduce failures to concurrency – Joining forks

11. Evaluation Setup 8 Clients + 4 Servers – Quad-core Intel Xeon 2.4 GHz – 8 GB RAM – Two local 7200 RPM disk – 2 clients are connected to each other! 1 Gbps link Each client issue 1 request / Minute

12. Variants Baseline – Clients trust the servers (no local data, no checks) B+hash – Clients attach hashes of values and verify hashes B+hash+Signing – Clients sign the values and verifies signatures B+hash+Signing+Store – Like B+hash+signing, plus locally store values that they put

13. Latency of Depot

14. Cost of Depot

15. Behavior Under Faults 50% Put, 50% Get Total server failure after 300 seconds

16. Fork by faulty clients 50% Reads, 50% Writes Failure after 300 seconds No effect on Get or Put

17. Conclusion Depot: Cloud storage with minimal trust Any node could fail in any way! Eliminate trust for – Put availability – Eventual consistency Minimize trust for – Get availability