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StarFish : highly-available block storage

StarFish : highly-available block storage. 資訊三 李益昌 B00902051 資訊三 何柏勳 B00902097. Introduction. Data protection Disk failure V.S. catastrophic site failure Low price of disk drives and high-speed networking infrastructure StarFish Survive catastrophic site failure

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StarFish : highly-available block storage

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  1. StarFish: highly-available block storage 資訊三李益昌B00902051 資訊三 何柏勳 B00902097

  2. Introduction • Data protection • Disk failure V.S. catastrophic site failure • Low price of disk drives and high-speed networking infrastructure • StarFish • Survive catastrophic site failure • Use IP network : (1) geographically-dispersed (2) inexpensive • Good performance • Block level

  3. Architecture • One Host Element(HE) • Provides storage virtualization and read cache • N Storage Element(SE) • Q: write quorum size. • Synchronous updates to a quorum of Q SEs, and asynchronous updates to the rest. • Communicate by TCP/IP over high speed network

  4. Architecture • Recommended configuration • N=3 Q=2

  5. Architecture • Another configuration

  6. Data consistency and SE recovery • Log • sequential number • NVRAM • Data consistency • Failure • RAID or network connection fails • SE recovery • Quick recovery • Replay recovery • Full recovery

  7. Availability and reliability analysis • Parameter • SE failure process : • SE recovery process : • Number of SEs : N • Quorum size : Q • Model • SEs failure process is i.i.d Poisson process with mean rate • SEs recovery process is i.i.d Poisson process with mean rate • HE failure process Poisson process with mean rate • HE recovery process Poisson process with mean rate

  8. Availability • a HE or SE is available if it can serve data • Availability of StarFish A(Q, N) : the steady-state probability that at least Q SEs are available • is called load , • Repairman model

  9. Availability(cont.)

  10. Availability(cont.) • SE availability = 1- • X★9:the number of 9s in an availability measure • Fixed N, availability decreases with large Q • Trade off availability for reliability

  11. Reliability • Probability of data loss • HE and Q SEs fails • The reliability increases with larger Q • Two approach • Q > floor(N/2) and at least Q SEs are available • Reduce availability • Read-only consistency

  12. Read-only consistency • Available in read-only mode during failure. • Read-only mode obviates the need for Q SEs to be available to handle updates. • Increase availability

  13. Availability with Read-only Consistency

  14. Implementation

  15. Performance measurements

  16. Setting • Gigabit Ethernet(GbE) with dummynet controlling delays and bandwith limit to model Internet links • Different network delays • 1, 2, 4, 8, 23, 36, 65 ms • Different bandwidth limitations • 31, 51, 62, 93, 124 Mb/s • Benchmark • Micro-benchmark • PostMark

  17. Effects of network delays and HE cache size • Larger cache improves performance • Larger cache doesn’t change the response time of write requests

  18. Normal Operation and placement of the far SE

  19. Normal Operation and placement of the far SE

  20. Normal Operation and placement of the far SE

  21. Observation • Performance is affected by two parameters • Write quorum size Q • Delay to the SE • StarFish performs adequately when one of the SEs is placed in a remote location • At least 85% of the performance of a direct-attached RAID

  22. Recovery • Performance degrades more during full recovery

  23. Conclusion • The StarFish system reveals significant benefits from a third copy of data at an intermediate distance • A StarFish system with 3 replicas, a write quorum size of 2, and read-only consistency yields better than 99.9999% availability assuming individual Storage Element availability of 99%

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