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Intelligent Placement of Datacenter for Internet Services

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Intelligent Placement of Datacenter for Internet Services

  1. 1. EEDC 34330Execution Intelligent Placement ofEnvironments for Datacenter for InternetDistributed ServicesComputingMaster in Computer Architecture,Networks and Systems - CANS Homework number: 6 by Arinto Murdopo –
  2. 2. Problem Statement where? dónde? di mana? oú? waar? Data Center dove? どこですか? πού? 在哪里?어디?Response time, availability,cost, environmental concerns 2
  3. 3. Proposed SolutionFramework Produce tool to compareSolve optimization efficiency and accuracyProblem Characterization 3
  4. 4. Framework Efficiently select data center locations Response Time Minimize Cost Consistency Availability 4
  5. 5. Solve Optimization ProblemProblem formulationApproaches:• Simple Linear Programming (LP0)• Pre-set Linear Programming (LP1)• Brute force (Brute)• Heuristic-based on LP (Heuristic)• Simulated Annealing plus LP1 (SA+LP1)• Optimzed SA + LP1 (OSA + LP1) 5
  6. 6. Placement ToolAvailable Inputs: MaxS 1/ratioServerUser MAXLAT MAXDELAY MINAVAIL area of interest Granularity existing data center 6
  7. 7. Placement ToolLocation-dependent data: Network backbones: latency data from backbone ISP Power plants, transmission lines, and CO2 emissions: obtained from DOE Electricity, land, water and temperature: obtained from DOE as well Missing data are obtained from neighboring location 7
  8. 8. Placement ToolDatacenter characteristics: Cooling : CRACs and Water Chillers for cooling Connection: It costs $500k/mile of transmission line, and $480k/mile of fiber. Amortization of 12 years Building: Its costs depends of the maximum power Land: 6 K square feet per Megawatt 8
  9. 9. Placement ToolDatacenter characteristics: Water: 24K gallons of water per MW per day Server: Each server costs $2000 (4 years amortization), each interconnect switch costs $20K (4 years amortization) Staff: $0.05 per Watt per month. $100K per year salary for 1K servers 9
  10. 10. CharacterizationCharacterize 7 locations in US 10
  11. 11. CharacterizationEvaluate each location with Placement ToolsParameters 11
  12. 12. Characterization Evaluate each location with Placement Tools Parameters 12
  13. 13. Broadening The ScopeDistribution of cost assuming 500 potential locations 13
  14. 14. Sample OutputSpecifications: Results1. 60 K servers Three locations :2. Latency <= 60 ms 1. Seattle(A, 1789 servers)3. Consistency Delay <= 85 ms 2. St. Louis (B, 22712 servers)4. Minimum Availability = 5 nines 3. Oklahoma city(C, 5501 servers) 14
  15. 15. Evaluation of Chosen ApproachBased on this specification:1. 60 K servers2. Latency <= 60 ms3. Consistency Delay <= 85 ms4. Minimum Availability = 5 nines 15
  16. 16. Overall cost table (in million) 16
  17. 17. Evaluation of Chosen ApproachRunning Times of Solution Approaches 17
  18. 18. Evaluation of Chosen ApproachSolution Quality 18
  19. 19. Evaluation of Chosen ApproachRecommended approach:OSA + LP1, since it provides best tradeoff betweenrunning time and search quality 19
  20. 20. Exploring Placement Tradeoff LatencyLatency of 50 ms strikes the best compromise between latency and cost 20
  21. 21. Exploring Placement Tradeoff AvailabilityIt is usually cheaper to build networks out of less redundant datacentersTier II data centers are the best option 21
  22. 22. Exploring Placement TradeoffConsistency Delay Low latency and low consistency are conflicting goals 22
  23. 23. Exploring Placement TradeoffGreen datacenters Green network is less than $100k more expensive per month than the cost-optimal network when the maximum latency can be relatively high (> 70ms) 23
  24. 24. Exploring Placement TradeoffChiller-less data center Avoiding chillers reduces costs by 8% for max latencies >= 70ms 24
  25. 25. Conclusions• Proposed and implemented optimization framework for automatic data center placement for Internet Services• Characterized US regions• Evaluated solutions based on the framework 25
  26. 26. Questions and answers 26