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Replica Placement Strategy for Wide-Area Storage Systems

Replica Placement Strategy for Wide-Area Storage Systems. Byung-Gon Chun and Hakim Weatherspoon RADS Final Presentation December 9, 2004. Environment. Store large quantities of data persistently and availably Storage Strategy Redundancy - duplicate data to protect against data loss

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Replica Placement Strategy for Wide-Area Storage Systems

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  1. Replica Placement Strategy for Wide-Area Storage Systems Byung-Gon Chun and Hakim Weatherspoon RADS Final Presentation December 9, 2004

  2. Environment • Store large quantities of data persistently and availably • Storage Strategy • Redundancy - duplicate data to protect against data loss • Place data throughout wide area for availability and durability • Avoid correlated failures • Continuously repair loss redundancy as needed • Detect permanent node failures and trigger data recovery

  3. Assumptions • Data is maintained on nodes, in the wide area, and in well maintained sites. • Sites contribute resources • Nodes (storage, cpu) • Network - bandwidth • Nodes collectively maintain data • Adaptive - Constant change, Self-organizing, self-maintaining • Costs • Data Recovery • Process of maintaining data availability • Limit wide area bandwidth used to maintain data

  4. Challenge • Avoiding correlated failures/downtime with careful data placement • Minimize cost of resources used to maintain data • Storage • Bandwidth • Maximize • Data availability

  5. Outline • Analysis of correlated failures • Show that correlated failures exist - are significant • Effects of common subnet (admin area, geographic location, etc) • Pick a threshold and extra redundancy • Effects of extra redundancy • Vary extra redundancy • Compare random, random w/ constraint, and oracle placement • Show that margin between oracle and random is small

  6. Analysis of PlanetLab Trace characteristics • Trace-driven simulation • Model maintaining data on PlanetLab • Create trace using all-pairs ping* • Collected from February 16, 2003 to October 6, 2004 • Measure • Correlated failures v. time • Probability of k nodes down simultaneously • {5th Percentile, Median} number of available replicas v. time • Cumulative number of triggered data recovery v. time *Jeremy Stribling http://infospect.planet-lab.org/pings

  7. Analysis of PlanetLab II Correlated failures

  8. Analysis I - Node characteristics

  9. Analysis II- Correlated Failures

  10. Correlated Failures

  11. Correlated Failures (machine with downtime <= 1000 slots)

  12. Availability Trace

  13. Replica Placement Strategies • Random • RandomSite • Avoid to place multiple replicas in the same site • A site in PlanetLab is identified by 2B IP address prefix. • RandomBlacklist • Avoid to use machines, in blacklist, that are top k machines with long down time • RandomSiteBlacklist • Combine RandomSite and RandomBlacklist

  14. Comparison of simple strategies(m=1, th=9, n=14, |blacklist|=35)

  15. Simulation setup • Placement Algorithm • Random vs. Oracle • Oracle strategies • Max-Lifetime-Availability • Min-Max-TTR, Min-Sum-TTR, Min-Mean-TTR • Simulation Parameters • Replication m = 1, threshold th = 9, total replicas n = 15 • Initial repository size 2TB • Write rate 1Kbps per node and 10Kbps per node • 300 storage nodes • System increases in size at rate of 3TB and 30TB per year, respective. • Metrics • Number of available nodes • Number of data repairs

  16. Comparison of simple strategies(m=1, th=9)

  17. Results - Random Placement(1Kbps)

  18. Results - Oracle Max-Lifetime-Avail(1Kbps)

  19. Results - Breakdown of Random (1Kbps)

  20. Results - Random(10Kbps)

  21. Results - Breakdown of Random (10Kbps)

  22. Conclusion • There does exist correlated downtimes. • Random is sufficient • A minimum data availability threshold and extra redundancy is sufficient to absorb most correlation.

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