Green Cloud Computing


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On June 24th I presented to the Dependable Systems Engineering group here in the School of Computer Science, St Andrews. The group meets once a month for a presentation from one of its members over lunch. The presenter talks about their current research, providing a good opportunity to keep up to date with other work within the group.On June 24th I presented to the Dependable Systems Engineering group here in the School of Computer Science, St Andrews. The group meets once a month for a presentation from one of its members over lunch. The presenter talks about their current research, providing a good opportunity to keep up to date with other work within the group.

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Green Cloud Computing

  1. 1. Energy Aware Clouds <ul><li>James W. Smith </li></ul><ul><li>[email_address] </li></ul>
  2. 2. Introduction <ul><li>Total Carbon Footprint of the IT industry was 2% of all human activity in 2007 </li></ul><ul><ul><li>830 MtCO2e </li></ul></ul><ul><ul><li>Energy powering devices is 75% of this total </li></ul></ul><ul><ul><li>Need to build sci-fi power or improve efficiency </li></ul></ul><ul><li>IT is beginning to learn that cutting emissions and cutting costs go naturally together </li></ul>
  3. 3. Costs <ul><li>Operational costs exceeding purchase costs </li></ul><ul><ul><li>Mainly driven by energy costs </li></ul></ul><ul><ul><li>Even over a relatively short lifespan </li></ul></ul>
  4. 4. so who benefits?
  5. 5. Roadmap <ul><li>Energy Aware Computing </li></ul><ul><li>Cloud Computing </li></ul><ul><ul><li>Private Clouds </li></ul></ul><ul><ul><li>Virtualisation </li></ul></ul><ul><li>Datacentres </li></ul><ul><ul><li>PUE & Productivity </li></ul></ul><ul><ul><li>Cooling </li></ul></ul><ul><li>Research areas for Energy Efficient Cloud Computing </li></ul><ul><ul><li>Monitoring </li></ul></ul><ul><ul><li>Resource Scaling </li></ul></ul><ul><ul><li>Smart Load Balancing </li></ul></ul><ul><ul><li>Task Consolidation </li></ul></ul><ul><li>Power Efficient Software </li></ul><ul><li>Future Work </li></ul>
  6. 6. Energy Aware Computing <ul><li>Attempting to address problems of energy efficiency in Computing Systems </li></ul><ul><ul><li>processor chips </li></ul></ul><ul><ul><li>cooling </li></ul></ul><ul><li>The overall problem is to “minimise energy used to perform a certain piece of useful work” </li></ul><ul><ul><li>Control resource availability </li></ul></ul><ul><ul><li>Reduce consumption </li></ul></ul>
  7. 8. Green Cloud? Positive Negative <ul><li>Datacentres can become the most efficient centres for computation yet </li></ul><ul><li>Providers will want to increase cost effectiveness </li></ul><ul><li>and be green! </li></ul><ul><li>Datacentres are now consuming 0.5% of all electricity in the world . </li></ul><ul><li>This will only continue to grow! </li></ul>
  8. 9. Private Cloud <ul><li>Private Cloud Systems have been likened to </li></ul><ul><li>However, Enterprise does have concerns about Cloud systems which Private Clouds can help to address </li></ul><ul><ul><li>Security </li></ul></ul><ul><ul><li>Privacy </li></ul></ul><ul><ul><li>Administrative Control </li></ul></ul>“ drinking on your own and calling it a private party” - P Laudenslager, (unknown)
  9. 10. Virtualization <ul><li>Virtualization makes clouds run </li></ul><ul><ul><li>Run multiple VMs on each physical machine </li></ul></ul><ul><ul><li>Improves utilization, cost effectiveness </li></ul></ul><ul><li>Save Energy </li></ul><ul><ul><li>Increase Utilization </li></ul></ul><ul><ul><li>Migrate work? </li></ul></ul><ul><ul><li>Power down unused machines </li></ul></ul><ul><ul><li>Allocated tasks appropriately? </li></ul></ul>
  10. 11. Virtualization (2) <ul><li>Performance overhead </li></ul><ul><ul><li>intermediate layer </li></ul></ul><ul><ul><li>increased complexity </li></ul></ul><ul><li>Different tasks have different performance costs </li></ul><ul><ul><li>for example, using the same physical disk for two or more VMs... </li></ul></ul><ul><ul><li>and different power consumptions... </li></ul></ul>
  11. 12. Virtualization (3) <ul><li>VMs increase utilization, power consumption & heat on a physical machine </li></ul><ul><li>So we need to be careful how much virtualization we do, where we do it and how we prepare for it </li></ul><ul><li>Is it possible to virtualize in an efficient manner? </li></ul>
  12. 15. Is this new? John McCarthy (1961): “ computation may someday be organised as a public utility”
  13. 16. Datacentres <ul><li>The age of the datacentre is here </li></ul><ul><li>One man and a credit card can tap into some of the largest computing resources in the world </li></ul>
  14. 17. Some figures <ul><li>Datacentres in the USA consume 1.5% of all electricity in that country </li></ul><ul><li>Energy consumption in this area has doubled in the period 2000-2006 </li></ul><ul><li>Only 50% of electricity consumed can be attributed to useful work done by servers, rest goes on cooling, infrastructure etc </li></ul>United States Environmental Protection Agency (EPA) 2007
  15. 18. Cheap power isn’t always green <ul><li>Allow me to be a hippie for a second... </li></ul>
  16. 19. Power Usage Effectiveness <ul><li>PUE compares how much energy is used by computing and infrastructure equipment </li></ul><ul><li>Perfect efficiency would give PUE of 1.0 </li></ul><ul><li>Most datacentres in the range 1.3 -> 3.0 </li></ul>PUE = Total Facility Power / IT Equipment Power
  17. 20. Datacentre Productivity <ul><li>PUE is useful but it doesn’t determine productivity over power </li></ul><ul><li>Step in the Datacentre Productivity Measurement: </li></ul><ul><li>Useful, as EAC likes to think of doing a task for least amount of power </li></ul><ul><li>But how would you measure Useful work? </li></ul>Datacentre Productivity = Useful Work / Total Facility Power
  18. 21. Cooling <ul><li>Why do we need to cool? </li></ul><ul><ul><li>Preserve lifetime of components </li></ul></ul><ul><li>Mechanical Engineering </li></ul><ul><ul><li>Air or water? </li></ul></ul><ul><ul><li>Direct Heat Exchange </li></ul></ul><ul><li>Computer Science </li></ul><ul><ul><li>Smart load balancing? </li></ul></ul>
  19. 22. Research Areas
  20. 23. Monitoring <ul><li>Reports have estimated that only 13.4% of organisations monitor their energy consumption! </li></ul><ul><li>Each component in a system must expose their consumption information </li></ul><ul><ul><li>and control mechanisms? </li></ul></ul><ul><li>If such functionality doesn’t exist then 3rd party tool needed </li></ul><ul><ul><li>Yi Yu </li></ul></ul><ul><ul><li>additional complexity </li></ul></ul><ul><ul><li>Software? Hardware? </li></ul></ul><ul><li>A controller can use this information to manage the system </li></ul>
  21. 24. Combining Computation and Cooling <ul><li>Traditionally, Cooling & Computation are controlled independently </li></ul><ul><li>Cooling uses CRAC units to cool datacentre to optimum operating temperature </li></ul><ul><li>Computational load is distributed to give best performance </li></ul><ul><li>However, Parolini et al suggest that workload can be distributed smartly according to temperature </li></ul><ul><ul><li>requires unified framework </li></ul></ul>“ Reducing Data Center Energy Consumption via Coordinated Cooling and Load Management” - Parolini, et al 2008
  22. 25. Powering Management <ul><li>Switch off your lights!!! </li></ul><ul><ul><li>Well, at least migrate your systems between power states </li></ul></ul><ul><li>How much do we switch off? </li></ul><ul><ul><ul><li>Laptop </li></ul></ul></ul><ul><ul><ul><ul><li>sending to sleep still costs energy </li></ul></ul></ul></ul><ul><ul><ul><ul><li>shutting down save more at the cost of additional time </li></ul></ul></ul></ul>Performance & Response Time vs. Energy Savings
  23. 26. Resource Scaling <ul><li>Use only the amount of resource required to complete a task </li></ul><ul><ul><li>Give each task a deadline </li></ul></ul><ul><ul><li>Only give resources to allow completion within that deadline </li></ul></ul><ul><li>Speed Scaling </li></ul><ul><ul><li>Adjust CPU speed </li></ul></ul><ul><ul><li>Save energy & cooling costs </li></ul></ul><ul><li>Fine for individual components, but how do we do this on a system-wide scale? </li></ul>Speed then time and power
  24. 27. Task Consolidation <ul><li>Keep machines well utilised </li></ul><ul><li>Bin packing problem </li></ul><ul><ul><li>Tasks are objects </li></ul></ul><ul><ul><li>Servers are bins </li></ul></ul><ul><ul><li>Resources are dimensions </li></ul></ul><ul><li>Relies upon being able to accurately predict tasks resource requirements </li></ul><ul><ul><li>performance adjusting applications? </li></ul></ul>
  25. 28. Load Balancing 14 University of St Andrews School of Computer Science <ul><li>Traditional model </li></ul><ul><li>Distribute work evenly </li></ul><ul><li>Each node has equal workload </li></ul>
  26. 29. Load Skewing 15 University of St Andrews School of Computer Science <ul><li>Energy efficient model </li></ul><ul><ul><li>“ Skew” load </li></ul></ul><ul><ul><li>Give work to nodes while they can handle it </li></ul></ul><ul><ul><li>Power down unused nodes </li></ul></ul>
  27. 30. Power Efficient Software 16 University of St Andrews School of Computer Science <ul><li>Different devices consume different amounts of energy doing (roughly) the same task. </li></ul><ul><ul><li>i.e. Making a call, playing a song </li></ul></ul><ul><ul><li>Why? Difference in hardware & Difference in software implementation </li></ul></ul><ul><li>Is it possible to produce energy efficient software? </li></ul><ul><ul><li>Optimise for time, scalability, robustness, but energy? </li></ul></ul>
  28. 31. PES Principles <ul><li>Useful work corresponds to resources consumed </li></ul><ul><li>Event-based architecture over polling </li></ul><ul><li>Light on memory </li></ul><ul><li>Batch I/O requests </li></ul>Software Modularity?
  29. 32. My Work
  30. 33. StACC Private Cloud <ul><li>So when the StACC cloud works what does it offer? </li></ul><ul><ul><li>a platform for experimentation </li></ul></ul><ul><li>We can control </li></ul><ul><ul><li>architecture </li></ul></ul><ul><ul><li>longitivity </li></ul></ul><ul><ul><li>number of nodes </li></ul></ul><ul><ul><li>exact workload </li></ul></ul>
  31. 34. Future Work <ul><li>Monitor VM performance </li></ul><ul><ul><li>Performance and Energy Consumption </li></ul></ul><ul><ul><li>Write Resource Monitoring Software </li></ul></ul><ul><li>Energy-Smart Control Algorithms for Clouds? </li></ul><ul><ul><li>Based on what? Utilisation? Consumption? Mix? </li></ul></ul><ul><li>Modify Eucalyptus open source software? </li></ul>
  32. 35. Research Question <ul><li>Can Cloud Computing have a positive impact on the energy efficiency of IT systems & can private clouds be made more energy efficient? </li></ul>
  33. 36. Questions?