Reliability Modeling and Analysis of Energy-Efficient Storage Systems

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With the rapid growth of the production and storage of large scale data sets it is important to investigate methods to drive the cost of storage systems down. Many
energy conservation techniques have been proposed to achieve high energy efficiency
in disk systems. Unfortunately, growing evidence shows that energy-saving schemes in disk drives usually have negative impacts on storage systems. Existing reliability models are inadequate to estimate reliability of parallel disk systems equipped with energy conservation techniques. To solve this problem, we firstly propose a mathematical model - called MINT - to evaluate the reliability of a parallel disk system where energy-saving mechanisms are implemented. In this dissertation, MINT is focused on modeling the reliability impacts of two well-known energy-saving techniques - the Popular Disk Concentration technique (PDC) and the Massive Array of Idle Disks (MAID). Different from MAID and PDC which store a complete file on the same disk, the Redundancy Array of Inexpensive Disks (RAID) stripes file into several parts and stores them on different disks to ensure higher parallelism, hence higher I/O performance. However, RAID faces more challenges on energy efficiency
and reliability issues. In order to evaluate the reliability of power-aware RAID, we
then develop a Weibull-based model–MREED. In this dissertation, we use MREED to model the reliability impacts of a famous energy efficiency storage mechanism– the Power-Aware RAID (PARAID). Thirdly, we focus on validation of two models–MINT and MREED. It is challenging to validate the accuracy of reliability models, since we are unable to watch certain energy-efficiency systems for a couple of decades due to its time consuming and experimental costs. We introduce validated storage system
simulator–DiskSim–to determine if our model and DiskSim agree with one another. In our validation process, we compare a file access trace in a real-world file system. Last part of of this dissertation focuses on improvement of energy-efficient parallel storage systems. We propose a strategy–Disk Swapping–to improve disk reliability by alternating disks storing data that is frequently accessed with disks holding less accessed data. In this part, we focus on studying reliability improvement of PDC and MAID. At last, we further improve disk reliability by introducing multiple disk
swapping strategy.

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  • Hot data--the data has increasing access rate Cold data--the data hasn’t been accessed for a while-- has decreasing access rate Most popular disk-- stores most of the hot data Least popular disk-- stores most of the cold data
  • Cache Disks only handle the data copied in while Data Disks only handle the data copied out
  • many of the applications are read-only eg. server system like youtube.com, more downloading than uploading
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • from access rate-utilization model, the higher the access rate is, the higher the utilization of the system will be, however from the utilization-AFR model,
  • The AFR of MAID will NOT keep decreasing At high access rate, AFR of MAID-1 is higher than that of MAID-2 the reason is on the following slide
  • Workload: 1, file accessing 2, file movement 3, parity data (for level 5)
  • problems that needs to be solved
  • problems that needs to be solved
  • problems that needs to be solved
  • problems that needs to be solved
  • many of the applications are read-only eg. server system like youtube.com, more downloading than uploading
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • Utilization Sensitivity: PDC is higher than MAID; AFR: when the access rate is low, PDC is lower than MAID the reason is on the following slide
  • why use benchmark to validate: unpractical to run in the real-life; sample size is still small why only validate access rate-utilization model: utilization-AFR base on maintenance data from report
  • why modeling reliability of PARAID? RAID with energy saving scheme failure of disk will have more problems: total data lose(raid 0) or more time and energy consuming for data recovering(raid 5)
  • why not improving reliability of PARAID? Reliability of RAID with energy saving scheme is still under research Level 0, hardly no improving space Level 1, need to find the balance point for energy vs. Reliability Level 5, complexity, performance, energy, and reliability
  • Reliability Modeling and Analysis of Energy-Efficient Storage Systems

    1. 1. Reliability Modeling and Analysis of Energy-Efficient Storage Systems Shu Yin Advisor: Dr. Xiao Qin Committee Members: Dr. Sanjeev Baskiyar Dr. Alvin Lim University Reader: Dr. Shiwen Mao
    2. 2. Presentation Outline• Motivation• MINT Model• MREED Model• Models Validation• Reliability Improvement• Conclusion and Future Work 2
    3. 3. MotivationStream Multimedia Bioinformatic 3D Graphic Weather Forecast Data Intensive Applications 3
    4. 4. Data Intensive Computing Application Cluster System 4
    5. 5. Problem: Energy DissipationEPA Report to Congress on Server and Data Center Energy Efficiency, 2007 5
    6. 6. Problem:Energy Dissipation(cont.) Using 2010 Historical Trends Scenario Disk • Data Centers consume 110 Syste Billion kWh per Year; m 27% • Assume Average Commercial End User Is Charged ¢9.46 per kWh • Disk System Can Account for 27% of the Computing Energy Other 73% Cost of Data Centers. Disk System May Have An Electrical Cost of 2.8 Billion Dollars! 6
    7. 7. Existing Energy Conservation TechniquesSoftware-Directed Power ManagementDynamic Power ManagementRedundancy TechniqueMulti- speed SettingHow Reliable Are They? 7
    8. 8. Contradictory of Energy Efficiency and Reliability Energy Efficiency Reliability Example: Disk Spin Up and Down 8
    9. 9. Presentation Outline• Motivation• MINT Model• MREED Model• Models Validation• Reliability Improvement• Conclusion and Future Work 9
    10. 10. MINT(MATHEMATICAL RELIABILITY MODELS FOR ENERGY-EFFICIENT PARALLEL DISK SYSTEMS) Energy Conservation Techniques Single Disk Reliability Model System-Level Reliability Model 10
    11. 11. MINT (Single Disk) Disk Age TemperatureFrequency Utilization Single Disk Reliability Model Reliability of Single Disk 11
    12. 12. MINT (Single Disk)R=α*BaseValue[1]*TemperatureFactor+β*FrequencyAdder[2] α and β are two coefficients to R Assumption: α = β = 1 in our research [1] E. Pinheiro, W.-D. Weber, and L.A. Barroso. Failure trends in a large disk drive population. Proc. USENIX Conf. File and Storage Tech., February2007. [2] IDEMA Standards. Specification of hard disk drive reliability. 12
    13. 13. MINT (Single Disk)R=α*BaseValue*TemperatureFactor+β*FrequencyAdderUtilization Impact on AFR Temperature Impact on Transition Frequency Impact on Temperature Factor Frequency Adder 13
    14. 14. MINT (Single Disk)R=α*BaseValue*TemperatureFactor+β*FrequencyAdder Frequency=350/Month, T=40°C Frequency=250/Month, T=40°C Frequency=350/Month, T=35°C Frequency=250/Month, T=35°C Base Value from Google Report[3] Single Disk Reliability[3] E. Pinheiro, W.-D. Weber, and L.A. Barroso. Failure trends in a large disk drive population. Proc.USENIX Conf. File and Storage Tech., February 2007. 14
    15. 15. MINT (Energy Conservation Techniques- PDC) Popular Date Concentration (PDC)[3] - cold data System Structure - hot data[3] E. Pinheiro and R. Bianchini. Energy conservation techniques for disk array-based servers. Int’l Conf.on Supercomputing, pages 68–78, June 2004. 15
    16. 16. MINT (Energy Conservation Techniques- PDC)Access Rate<MIN(Access Rate) Access Rate>MAX(Access Rate) Access Rate<MIN(Access Rate) More Popular Disk Less Popular Disk Access Rate>MAX(Access Rate) - cold data - hot data 16
    17. 17. MINT (Energy Conservation Techniques- PDC) Popular Date Concentration (PDC)[3] - cold data System Structure - hot data (Optimal Result for Certain Time Phases) 17
    18. 18. MINT (Energy Conservation Techniques- MAID) Massive Array of Idle Disks (MAID)[4] - cold data System Structure - hot data[4] Dennis Colarelli and Dirk Grunwald. Massive arrays of idle disks for storage archives.Supercomputing ’02: Proceedings of the 2002 ACM/IEEE conference on Supercomputing, pages 1–11,Los Alamitos, CA, USA, 2002. IEEE Computer Society Press. 18
    19. 19. MINT (Energy Conservation Techniques- MAID) Cache Disk Data Disk Access Rate>MAX(Access Rate) Massive Array of Idle Disks (MAID)[4] - cold data System Structure - hot data[4] Dennis Colarelli and Dirk Grunwald. Massive arrays of idle disks for storage archives.Supercomputing ’02: Proceedings of the 2002 ACM/IEEE conference on Supercomputing, pages 1–11,Los Alamitos, CA, USA, 2002. IEEE Computer Society Press. 19
    20. 20. MINT (System-Level) Access Disk Age Temperature Pattern Energy Conservation TechniquesFrequency Utilization Frequency Utilization Single Disk Reliability Model Reliability of Reliability of Disk 1 Disk n System-Level Reliability Model Reliability of A Parallel Disk System 20
    21. 21. Preliminary Results (experimental setting) Energy-efficiency File Access Rate File Size Number of Disks Scheme (No. per month) (KB) 20 data PDC 0~106 300 (20 in total) 15 data + 5 cache MAID-1 0~106 300 (20 in total) 20 data + 5 cache MAID-2 0~106 300 (25 in total)Read-only Disks 21
    22. 22. Preliminary ResultComparison Between PDC and MAID AFR Comparison of PDC and MAID Access Rate(*104) Impacts on AFR (T=35°C) 22
    23. 23. Preliminary ResultComparison Between PDC and MAID AFR Comparison of PDC and MAID Access Rate(*104) Impacts on AFR (T=35°C) - PDC - MAID 23
    24. 24. MAID under High Access Rate MAID-1 MAID-2 AFR Comparison of PDC and MAID Access Rate(*104) Impacts on AFR (T=35°C) 24
    25. 25. MAID under High Access Rate MAID-1 MAID-2 MAID-1 MAID-2 MAID-1 MAID-2 AFR Comparison of PDC and MAIDAccess Rate(*104) Impacts on AFR (T=35°C) 25
    26. 26. MINT (conclusion)Mathematical Model for Disk SystemsMINT Study on PDC and MAIDBut ... Data Stripping Mechanism Energy Consumption Issues What about RAID? Reliability Issues Complexity 26
    27. 27. Presentation Outline• Motivation• MINT Model• MREED Model• Models Validation• Reliability Improvement• Conclusion and Future Work 27
    28. 28. MREED Model(MATHEMATICAL RELIABILITY MODELS FOR ENERGY-EFFICIENT RAID SYSTEMS) Access Pattern Temperature Energy Conservation Techniques Utilization Frequency Weibull Analysis Annual Failure Rate 28
    29. 29. Weibull AnalysisA Leading Method for Fitting Life DateAdvantages: Accurate Small Samples Widely Used 29
    30. 30. MREED Model (Energy Conservation Techniques- PARAID) Soft State RAID Gears 1 2 3 Power-Aware RAID (PA-RAID)[5] System Structure[5] Charles Weddle, Mathew Oldhan, Jin Qian, An-I Andy Wang.PARAID: A Gear-Shifting Power-Aware RAID.USENIX FAST 2007. 30
    31. 31. Reliability Evaluation(Experiment Setup) Disk Type Seagate ST3146855FC Capacity 146 GB Cache Size Sata 16MBBuffer to Host Transfer Rate 4Gb/s (Max) Total Number of Disks 5 File Size 100 MB Number of Files 1000 Synthetic Trace Poisson Distribution Time Period 24 HoursInterval Time (Time Phase) 1 Hour Power on Hour Per Year 8760 Hours 31
    32. 32. Reliability Evaluation (Disk Utilization Comparison)Disk Utilization Comparison Between PARAID-0 and RAID-0 at A Low Access Rate (20/hr) 32
    33. 33. Reliability Evaluation (Disk Utilization Comparison)Disk Utilization Comparison Between PARAID-0 and RAID-0 at A High Access Rate (80/hr) 33
    34. 34. Reliability Evaluation (AFR Comparison)AFR Comparison Between PARAID-0 and RAID-0 at A Low Access Rate (20/hr) 34
    35. 35. Reliability Evaluation (AFR Comparison) AFRAFR Comparison Between PARAID-0 and RAID-0 at A High Access Rate (80/hr) 35
    36. 36. Presentation Outline• Motivation• MINT Model• MREED Model• Models Validation• Reliability Improvement• Conclusion and Future Work 36
    37. 37. Model ValidationTechniques– Run the Systems for A Couple of Decades– The Event Validity Validation Techniques[6] [6] R.G. Sargent, “Verification and Validation of Simulation Models”, in Proceedings of the 37th conference on Winter Simulation, ser. WSC’05 Winter Simulation Conference, 2005. 37
    38. 38. Model ValidationChallenges Unable to Monitor PARAID Running for Years Sample Size is Small from A Validation Perspective (e.g. 100 Disks for Five Years) 38
    39. 39. Model Validation (DiskSim[7] Simulation) File To Block Level Converter [7] S.W.S John, S. Bucy, Jiri Schindler and G.R. Ganger, “The DiskSim Simulation Environment Version 4.0 Reference Manual”, 2008 39
    40. 40. Model Validation (DiskSim Simulation) Diagram of the Storage System Corresponding to the DiskSim RAID-0 40
    41. 41. Model Validation (Result)Utilization Comparison Between MREED and DiskSim Simulator 41
    42. 42. Model Validation (Result)Gear Shifting Comparison Between MREED and DiskSim Simulator 42
    43. 43. Presentation Outline• Motivation• MINT Model• MREED Model• Models Validation• Reliability Improvement• Conclusion and Future Work 43
    44. 44. Recall PDC Popular Date Concentration (PDC) - cold data System Structure - hot data (Optimal Result for Certain Time Phases) 44
    45. 45. Problem of PDC The Most Popular Disk:High AFRNo Replica 45
    46. 46. Reliability Improvement of PDCMethod of Improving Reliability MirroringExtra Disks for Replication -> More Energy Consumption Disk SwappingSwap Existing Disks 46
    47. 47. Disk Swapping Scheme PDCSwap the Most Popular Disk with the Least Popular Disk 47
    48. 48. Disk Swapping Scheme PDCSwap the Highest AFR Disk with the Lowest AFR Disk 48
    49. 49. Disk Swapping Scheme MAID Swap the Cache Disks with the Data Disks 49
    50. 50. Preliminary Results (experimental setting) Energy-efficiency File Access Rate File Size Number of Disks Scheme (No. per month) (KB) 20 data PDC 0~106 300 (20 in total) 15 data + 5 cache MAID-1 0~106 300 (20 in total) 20 data + 5 cache MAID-2 0~106 300 (25 in total)• Read-only Disks• Mean Time to Data Lose (MTTDL)• Swapping Thresholds (2*105, 5*105, 8*105 No./Month)• Single Swapping 50
    51. 51. Comparison of Disk Swap PDC AFR Comparison of PDC Access Rate(*104) Impacts on AFR (T=35°C) Threshold = 2*105 No./Month 51
    52. 52. Comparison of Disk Swap PDC AFR: Swap2 < Swap1 < No Swap AFR Comparison of PDC Access Rate(*104) Impacts on AFR (T=35°C) Threshold = 2*105 No./Month 52
    53. 53. Comparison Between Different Threshold PDC AFR Comparison of PDC Access Rate(*104) Impacts on AFR (T=35°C) Threshold = 2*105 No./Month 53
    54. 54. Comparison Between Different Threshold PDC AFR Comparison of PDC Access Rate(*104) Impacts on AFR (T=35°C) Threshold = 5*105 No./Month 54
    55. 55. Comparison Between Different Threshold PDC AFR Comparison of PDC Access Rate(*104) Impacts on AFR (T=35°C) Threshold = 8*105 No./Month 55
    56. 56. Comparison Between Different Threshold PDCAFRHigher Threshold -> Lower AFR AFR Comparison of PDC Access Rate(*104) Impacts on AFR (T=35°C) Threshold = 2*105 No./Month, 5*105 No./Month, 8*105 No./Month 56
    57. 57. Limitations• Read Only Disk Scenario• Data Migration within Certain Time Phases• Simple File Access Patterns 57
    58. 58. Future Work Extend the Models to investigate mixed read/write workloads; Research the trade-offs between reliability and energy- efficiency; Extend schemes to a real-world based environment; Develop a multi-swapping mechanismbalancing the utilization & lowering the failure rate; Evaluate more control groups. 58
    59. 59. Conclusion• Generic Models coupled with power management optimization policies;• Two reliability models for the three well-known energy-saving schemes -- PDC, MAID and PARAID;• Disk swapping strategies to improve disk reliability for PDC. 59
    60. 60. Thanks
    61. 61. Questions?

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