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The StarFish system demonstrates a robust solution for highly available block storage, addressing both disk and site failures through innovative architecture. Utilizing IP networks, it offers geographical diversification, ensuring data protection at low costs. The design emphasizes storage virtualization, efficient recovery processes, and high performance, with configurations balancing quorum sizes for improved reliability. StarFish achieves over 99.9999% availability under optimal conditions, making it an excellent choice for critical data environments. Explore how this framework revolutionizes reliability and availability in data storage.
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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 • Use IP network : (1) geographically-dispersed (2) inexpensive • Good performance • Block level
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
Architecture • Recommended configuration • N=3 Q=2
Architecture • Another configuration
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
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
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
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
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
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
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
Effects of network delays and HE cache size • Larger cache improves performance • Larger cache doesn’t change the response time of write requests
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
Recovery • Performance degrades more during full recovery
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%