Energy efficient storage in vm

Lei Ye, Gen Lu, Sushanth Kumar,

Chris Gniady, John H. Hartman

Department of Computer Science

University of Arizona

Energy-Efficient Storage in

Virtual Machine Environments

1Xen Summit at AMD April 28-29, 2010

Energy is Critical

Energy consideration is critical for system design

Virtualization is becoming common in all platforms

Integration of virtualization and energy management is critical

for overall system efficiency

OS1

App

OSn

App…

VMM

OS1

App

OSn

App…

VMM

OS1

App

OSn

App…

VMM


Current Environment for Energy Management

OS is the central point for energy management

Global views of application execution

OS directly interacts with the hardware

Detailed hardware knowledge allows sophisticated energy

management

Physical

Hardware

Operating

Systems

Applications


Abstraction in Virtual Machines

Where should we manage energy?

OS only sees the virtualized hardware

VMM is unaware of the application execution

Separation of hardware and OS makes energy management a

challenge

Virtual Machine Monitor


Cross-layer Energy Optimization

Goals

Preserve VM abstractions

Adapt current energy optimization

Approach

Shape I/O accesses at VMM

Provide hints from VMM to the VMs

Outcome

Integrate existing disk energy management into VM


Outline

Introduction

Existing Mechanisms

Design

Evaluation

Conclusion


Existing Disk Energy Management

Goal: Maximize length of sleeping periods

Must exceed break-even time

Approach: Shaping write activities

Consequence:

Maximize disk off time

Reduce disk spin-ups

Last I/O New I/O

Timeout

starts

Timeout

expires

sleep

Spin-up

I/O Idle I/O

Spin-down


Buffer Cache

Function

Store data temporarily (default 30 seconds)

Perform data transfer for block device

Advantage

Trade disk accesses for memory accesses

Disadvantage

Loss of buffered data in case of system crash

Linux Kernel

File

System

Buffer

CacheApplications


Buffer Cache Complicates Timeout

Timeout might occur when there are pending writes

Disk spin-up might occur even in absence of application I/O

30 seconds

Timeout

starts

Timeout

expires

sleep

Spin-up

I/O I/O

App I/O

to buffer cache

Buffer cache

flush

Data delivered

to disk

Idle Idle


Early Flush

Do buffer flushes prior to shutdown

No impact on desired I/O reliability

I/O Idle

Idle

OS

I/O

I/O

Idle

Early Flush

Idle Idle

sleep

Physical

Disk state

Buffer Flush


Extended Buffering

Can extend idle time under writes

May impact I/O reliability

Idle Buffer Flush

I/O

30 seconds

Buffer being flushed

sleep sleepsleep

Extended idle time

Idle

Physical

Disk state

OS

IdleBuffer Flush I/OIdle


Buffer Flushes in Virtual Machines

Guest OS is unaware of physical disk state

Buffer flushes from VMs are unsynchronized

I/O Idle I/O

VM1

Buffer Flush

Buffer Flush Idle

VM2

I/O

I/O

Idle I/O Idle

Idle Idle

Idle

Idle Idle

Idle

IdleIdle

Physical

Disk state

I/O

sleep sleep sleep



Early Flush in Virtual Machines

Hints signal disk shutdown and trigger flush

Disk spin-ups avoided and disk idle time maximized

I/O Idle

VM1

Idle

VM2

I/O

I/O

Idle Idle Idle Idle IdleIdle

I/O

Idle

Early Flush Notification

Idle

Idle

Idle

Idle

sleep


Physical

Disk state

Buffer Flush

Buffer Flush


Buffering in Virtual Machine Monitor

Extend disk idle time

Buffer writes from VMs

Only when the disk is sleeping

Only one copy of data

Buffer is flushed when:

VMM buffer timeout (30 seconds)

Read request from a VM

Reads and sync from VMs are processed immediately

Impact I/O reliability


Evaluation Methodology

Trace collection

8 concurrent VMs as remote desktops on Xen

Users interact with VMs remotely via VNC

Rsyslog: timestamps of I/O activity, I/O type, access size,

domain identifier, process identifier, process name, and file

inode

Traces: 12 hours per VM

Common interactive applications

Disk drive:

WD2500JD: High performance drive, 9 s. long spin-up time


Disk I/O Trace Statistics

Configuration

1 VM – 1 user

2 VMs – 2 concurrent users



Number of

VMs

Number of

Reads

Number of

Writes

Number of

Idle Periods

Total Idle

Time [s]

1 62951 1339 255 40071

2 64886 17031 435 37470

4 83050 59407 601 31263

8 160049 103840 566 20450


Distribution of Idle Periods

0

100

200

300

400

500

600

700

2 4 8 16 32 64 128

1 VM 2 VMs 4 VMs 8 VMs

Time [Break-Even Period]

Num

ber

of

Idle

Per

iod

s


Energy Consumption

0

100

200

300

400

500

S B F BF S B F BF S B F BF S B F BF


Sleep

Power-Cycle

Active

Ener

gy C

onsu

mp

tio

n (

KJo

ule

s)

S-Standard, B-Buffering, F-Early Flush, BF-Buffering&Early Flush


Execution Time

0

2

4

6

8

10

12

14



Spin-up Idle > BE Active


Exec

uti

on T

ime

(Ho

urs

)


Reducing Spin-ups

0

100

200

300

400

500

600



Buffered Write

Write

Read


Num

ber

of

Sp

in-u

ps


Energy Delay Product

0

0.2

0.4

0.6

0.8

1

1.2



No

rmal

ized

Ener

gy D

elay

Pro

duct



Buffering in VMM with Immediate Sleep

The disk is put to sleep immediately after a buffer flush

VMM buffer flush independent from VM I/Os

Physical

Disk state

VM1

VM2

Idle Buffer Flush

VMM

Delayed Writes

I/O

Writes being buffered

30 seconds Buffer being flushed

Idle

Idle

sleep sleepsleep

Extended idle time

Idle Buffer Flush

Writes being buffered


Immediate Sleep Optimization

0

100

200

300

400

T I T I T I T I T I T I T I T I

B BF B BF B BF B BF


Sleep

Power-Cycle

Active

Ener

gy C

onsu

mp

tion (

KJo

ule

s)

B-Buffering, BF-Buffering&Early Flush, T-Timeout, I-Immediate


Writes in Buffering and Early Flush

Buffering in the VMM can result in additional delays

The longer the write resides the buffer, the higher the impact

on reliability

VMs Mechanisms Write Delay Delayed Writes Early Flush

Participants

1 Buffering

Early Flush

Buffering & Early Flush

14.5s

N/A

10.6s

3.5

N/A

1.9

N/A

1.0

1.0

2 Buffering

Early Flush


13.8s

N/A

14.0s

8.3

N/A

9.2

N/A

1.1

1.0

4 Buffering

Early Flush


13.8s

N/A

15.5s

11.3

N/A

9.8

N/A

1.2

1.2

8 Buffering

Early Flush


13.9s

N/A

13.2s

14.1

N/A

16.1

N/A

1.4

1.5


Conclusion

Existing energy optimizations require modification to be

effective in a VM environment

OS only sees the virtualized hardware

VMM is unaware of the application execution

Early Flush reduces spin-ups due to buffer flushes

Reduce energy by 10.5% compared with standard case in 8 VMs

VMM buffering extends disk idle time by delaying VM writes

Reduce energy by 7.7% compared with standard case in 8 VMs

Combination reduces energy consumption by 14.8% in 8 VMs


Q & A

Thank You

Energy efficient storage in vm

Technology

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