mri energy-efficient cloud computing

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Energy-Efficient Cloud Computing Walking towards a more energy-efficient computing world. Roger Rafanell 18/6/2012 MRI

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Page 1: MRI Energy-Efficient Cloud Computing

Energy-Efficient

Cloud Computing Walking towards a more energy-efficient computing world.

Roger Rafanell

18/6/2012

MRI

Page 2: MRI Energy-Efficient Cloud Computing

Outline

Energy-Efficient Cloud Computing

Part 1: Introduction Part 2: Current state of Energy-Efficiency Part 3: Towards Energy-Efficient Cloud Computing Part 4: Conclusions

Page 3: MRI Energy-Efficient Cloud Computing

Introduction

Data centre Costs by Amazon.com

“Data centre expenses related cost of operation the servers becomes the 57% of total budget while energy-

related costs amount to 31%.”

Page 4: MRI Energy-Efficient Cloud Computing

Introduction

Where does the energy goes?

Page 5: MRI Energy-Efficient Cloud Computing

Outline

Energy-Efficient Cloud Computing

Part 1: Introduction Part 2: Current state of Energy-Efficiency Part 3: Towards Energy-Efficient Cloud Computing Part 4: Conclusions

Page 6: MRI Energy-Efficient Cloud Computing

Current State

Data centre power distribution

Page 7: MRI Energy-Efficient Cloud Computing

Current State

Research community propose solutions for optimize each part of chain.

Page 8: MRI Energy-Efficient Cloud Computing

Current State

How DC can cut energy consumptions? • Energy-efficient opportunities for power consumption:

– Energy-efficient hardware

– Power minimization in Cluster & Networks

– Distributed Energy-Efficient Schedulers (DEES)

• Cooling consumptions can be cut by:

– Better air management

– Move to liquid cooling

– Use of free cooling (Green)!

Page 9: MRI Energy-Efficient Cloud Computing

Current State

Energy-efficient hardware • Processors Dynamic Speed & Voltage Scaling:

– SpeedStep (Intel)

– PowerNow (AMD)

– Cool’nQuiet (Dynamic fan speed)

• Advanced Configuration and Power Interface (ACPI)

• Other efficient emerging solutions:

– Solid State Disks

– Hibernation of hardware components

Page 10: MRI Energy-Efficient Cloud Computing

Current State

Power minimization on Clusters & Networks

“Components such as disks, memory or network devices also use energy when server is idle, still

using up to 60% of its peak power.”

How can be mitigated?

“According to some estimates, Internet may consume more than 860 TWh annually.”

Page 11: MRI Energy-Efficient Cloud Computing

Current State

Power minimization on Clusters & Networks

• Clusters

– Develop energy & economic criteria to dispatch jobs.

– Set part of servers down or to a low-power state.

– Use dynamic provisioning algorithms to obtain the minimum number of servers required respecting SLAs.

• Networks (seriously considered since recently)

– Energy-saving routing protocols for wireless networks.

– Research on topology control (real-time network graph modification).

– On-going development of new energy-efficient Ethernet standard (IEEE 802.3az).

Page 12: MRI Energy-Efficient Cloud Computing

Outline

Energy-Efficient Cloud Computing

Part 1: Introduction Part 2: Current state of Energy-Efficiency Part 3: Towards Energy-Efficient Cloud Computing Part 4: Conclusions

Page 13: MRI Energy-Efficient Cloud Computing

Efficient Cloud Computing

Energy-aware Clouds

• Currently based on:

– Virtualization

– Consolidation

– Improvement on Cooling

– Energy-awared software: Cloud applications, Cloud programming models, etc…

Page 14: MRI Energy-Efficient Cloud Computing

Efficient Cloud Computing

Virtualization

• Allows partition computational resources and share the hardware:

– Many services often needs only small fraction of computational resource.

– Low server utilization consumes non-less than 60% of peak power.

– This services can be virtualized running on a virtual machine.

– Virtual machines can be: created, terminated, cloned or moved from host to host.

Page 15: MRI Energy-Efficient Cloud Computing

Efficient Cloud Computing

Consolidation techniques

• Resource optimization:

– Many virtual machines can run on a single hardware unit (consolidation).

– Live-Migration: VM host-to-host migration while running in nanoseconds.

– Reduction on cooling due distributing properly the VMs over physical resources avoiding thermal hotspots.

Page 16: MRI Energy-Efficient Cloud Computing

Efficient Cloud Computing

Consolidation techniques

Page 17: MRI Energy-Efficient Cloud Computing

Efficient Cloud Computing

Cooling Improvements

• Thermal considerations:

– Of data centre interior structure (ceiling, walls, floor, …)

– For consolidation and virtualization purposes.

– For interference effects on neighbouring computing nodes.

– For correlate the temperature rise, load and power consumption.

Page 18: MRI Energy-Efficient Cloud Computing

Conclusions

The IT business future is going to Energy-awared Data centers and Green Computing.

Nowadays, one can leverage a lot of available energy-awared technologies and techniques at different levels.

Researchers comunity is currently starting to tackle energy-efficiency problems.

Savings on Green House Gas and CO2 emissions!!!

Page 19: MRI Energy-Efficient Cloud Computing

Doubts? [email protected]