50120140505011

International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),

ISSN 0976 - 6375(Online), Volume 5, Issue 5, May (2014), pp. 82-93 © IAEME

82

EMPIRICAL STUDY ON OFFLINE VS LIVE MIGRATION

Anala M R

Department of Computer Science and Engineering, R V College of Engineering

Bangalore, India

Shobha G

Department of Computer Science and Engineering, R V College of Engineering

Bangalore, India

ABSTRACT

Virtualization is a state-of-the-art technology facilitating resource optimizations by providing

an environment conducive to execute as many VMs as possible. The proliferation of VMs on a

physical server makes the resource management convoluted. This difficulty in managing the

resources results in these VMs not to perform optimally and seldom demonstrate poor performance.

Often this underperformance may result in the VM to fail and stop working. Hence, it becomes

necessary to migrate a VM from a source to a destination. When the migration decision has been

taken, it becomes necessary to analyze the performance of applications during migration since all the

applications will not exhibit the same performance during migration. The Migration can be

conducted offline or live. This paper aims at analyzing the performance of offline and live migration

techniques with respect to total migration time, downtime and performance of an application during

migration.

Keywords: Offline migration; Live migration; Performance; Migration time; Downtime.

I. INTRODUCTION

The virtualization technology’s main motivation is to run multiple and as many VMs as

possible to execute multiple tasks. As and when the number of VMs in a server increases, this surge

makes it difficult to manage the resources allocated to these VMs. The difficulty in resource

management results in underperformance of VMs. These VMs may collapse and fail to continue to

serve. To avoid breaking up of these VMs, it is necessary to migrate a running VM from source host

to destination host for balancing the load.

INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &

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ISSN 0976 – 6367(Print)

ISSN 0976 – 6375(Online)

Volume 5, Issue 5, May (2014), pp. 82-93

© IAEME: www.iaeme.com/ijcet.asp

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IJCET

© I A E M E

International Journal of Computer Engineering and Technology (IJCET), ISSN 0976

ISSN 0976 - 6375(Online), Volume 5, Issu

TYPES OF MIGRATION

Migration can be performed on the fly (live migration) or offline. In offline (stop and copy)

migration, VM running at the source is suspended and memory image is copied to the destination.

Figure 1 illustrates the working of stop and copy migration (offline). The steps i

copy migration is to stop VM running at source, migrate VM’s memory image from source to

destination and finally to start VM at destination.

Live migration is a process of moving the VM from one physical machine to another, on the

fly, keeping in mind to be as less disruptive as possible. Ideally, when live migration happens under

perfect conditions, it should be seamless i.e. the whole process should happen in an end user agnostic

manner. Live migration allows an administrator to take a

upgrading without subjecting the system's users to downtime. The goal is for an end user to not notice

the effect of live migration.

Figure 1

There are many algorithmic approaches to

this paper is to discuss pre-copy memory migration [1]. This paper analyzes the live migration

performance of pre-copy approach and offline migration for different applications. Figure 2 shows the

scenario before live migration and Figure 3, after live migration.

Figure 2 illustrates the process of live migration. Here, the memory ima

source host is copied to destination host in iterations. When both source and destination

synchronized i.e. maintain consistent copies, the VM image at source is destroyed and the VM

continues to run in destination as shown in Figure 3.


6375(Online), Volume 5, Issue 5, May (2014), pp. 82-93 © IAEME

83

performed on the fly (live migration) or offline. In offline (stop and copy)


Figure 1 illustrates the working of stop and copy migration (offline). The steps involved in stop and


destination and finally to start VM at destination.


keeping in mind to be as less disruptive as possible. Ideally, when live migration happens under


manner. Live migration allows an administrator to take a virtual machine offline for maintenance or


Figure 1: Stop and Copy migration

There are many algorithmic approaches to conduct VM memory migration, but the scope of

copy memory migration [1]. This paper analyzes the live migration

copy approach and offline migration for different applications. Figure 2 shows the

re live migration and Figure 3, after live migration.

Figure 2: Before migration

Figure 2 illustrates the process of live migration. Here, the memory image of VM running at

is copied to destination host in iterations. When both source and destination

consistent copies, the VM image at source is destroyed and the VM

continues to run in destination as shown in Figure 3.


performed on the fly (live migration) or offline. In offline (stop and copy)


nvolved in stop and



keeping in mind to be as less disruptive as possible. Ideally, when live migration happens under


virtual machine offline for maintenance or


conduct VM memory migration, but the scope of

copy memory migration [1]. This paper analyzes the live migration

copy approach and offline migration for different applications. Figure 2 shows the

ge of VM running at

is copied to destination host in iterations. When both source and destination are

consistent copies, the VM image at source is destroyed and the VM



84

Figure 3: After migration

II. LITERATURE SURVEY

As virtualization gains popularity for large computing environments, management of VMs is

becoming an important problem. The efficiency of the platform as well as the performance of

applications running on the platform is critically dependent on the characteristics of the applications

and the availability of required resources. If the required resources are not available at the source host

and the VM is under resource stress situation, then the VM has to be relocated for continued services.

The resource reallocation can be achieved using replication or migration. Replication allows creating

a replica of a virtual machine on another physical machine.

The first study on replication is conducted in [2]. This study compares both replication and

migration mechanisms. It concludes that replication is preferred over migration when the CPU usage

is high since migration process consumes computational resources. If the CPU usage is relatively low,

then the migration mechanism is used.Performance evaluation of both live and non-live migration

methods, presented in [3], demonstrates that the performance of processes running on a migrating

virtual machine severely declines in virtualized computing environment. The analysis revealed that a

host OS communication and memory writing between two hosts are the main reasons for the decline.

Live migration is a widely used technique for resource consolidation, fault tolerance, load

balancing and power saving. The research is carried out in multiple directions to achieve impressive

performance during live migration with respect to performance of an application running in VM, it’s

total migration time and the downtime experienced during live migration. The design for migrating

OSes running services with liveness constraints using the concept of writable working set is

demonstrated in [1]. Improved pre-copy approach using bitmap page to mark frequently updated

pages to ensures that frequently updated pages are transmitted only once in the iteration process is

introduced in [4]. Post-copy migration [5] defers the transfer of a VM’s memory contents until after

its processor state has been sent to the target host.

Research is ongoing in the area of improving performance of live migration. The various

factors like total migration time, downtime, page dirty rate etc. influences the performance of live

migration. The following text discusses the progress of the work towards this direction.

Link speed and page dirty rate [6] are the two parameters affecting the live migration

performance. The downtime is minimized in [7] using model called memory change Probability

Density Function (PDF) of the VM. The performance evaluation on the effects of live migration of

virtual machines based on the applications running inside Xen VMs are presented in [8].

Dynamic resource management for virtual machines using live migration techniques in cloud

environment is discussed [9]. Migration heuristics are categorized to reduce power consumption and

balancing load across physical machines. The impacts of different resource reservation methods on

the performance of live migration are investigated in [10]. To improve the resource utilization a new

live virtual machine migration strategy is proposed in [11] and using the characteristics of workloads,

hotspots are detected. The selection of migrating VM and destination host depends on multi-threshold

patterns.

To optimize consumption of energy, an approach is proposed to determine the best candidate

of migrating VM and also to choose a destination PM. The memory-compression based VM



migration approach [12] to compresses memory before migration is used to lessen migration time.

The behavior of pre-copy live migration for memory intensive

performance of live VM migration is studied [14

application-oblivious models were designed based on workload analysis at hypervisor level to predic

the cost of live migration [15]. This study estim

and energy. Affinity-aware migration technique [16

considering dynamism in network topology and job communication patterns.

III. PERFORMANCE ANALYSIS

During offline migration, the running VM instance is suspended and a snapshot of this suspended

memory image is moved from the source host to the destination host. The copied VM’s memory

image is resumed on the destination host and the memory the VM

Figure 4: Offline migration’s Total Migration Time(TMT) and Downtime(DT) for different

The drawback of offline migration is due to the fact that the services provided by that VM are

suspended for an interim duration equal to the total migration time and the total migration time

depends on the memory size of the VM

of offline migration for different applications.

IV. LIVE MIGRATION APPROACHES

Offline migration dictates that the currently running VM be suspended and this suspended

VM’s memory image be moved from a source host to a destination host. The copied VM’s memory

image is resumed on the destination host and the memory the VM used on the source host

the other hand, live migration facilitates migration of the VMs from a source host to destination host

on the fly. The administrators of data centres use live migration as an essential tool for high

availability of resources. Live migration f

balancing, and low-level system maintenance. Since live migration is performed on the fly, it results

in an impressive performance with minimal service downtimes. This section discusses pre copy

approach to achieve live migration.

A. LIVE MIGRATION USING PRE

This section discusses the idea behind pre

migration of virtual machines, the hypervisor is responsible to copy all the memory pages from the

source host to the destination host while the VM is still running on the source host. The frequently

updated pages, known as dirty pages are re

rate of re-copied pages is not less than page dirtyi



85

] to compresses memory before migration is used to lessen migration time.

copy live migration for memory intensive applications is analyzed in [13

live VM migration is studied [14] under different levels of resource availability. Two

oblivious models were designed based on workload analysis at hypervisor level to predic

]. This study estimates the cost of live migration based on performance

aware migration technique [16] allocates resources to virtual machines

considering dynamism in network topology and job communication patterns.

ANALYSIS OF OFFLINE MIGRATION



image is resumed on the destination host and the memory the VM used on the source host is freed.

Offline migration’s Total Migration Time(TMT) and Downtime(DT) for different

application


duration equal to the total migration time and the total migration time

depends on the memory size of the VM as shown in Figure 4. This section discusses the performance

of offline migration for different applications.

APPROACHES

ration dictates that the currently running VM be suspended and this suspended


image is resumed on the destination host and the memory the VM used on the source host



availability of resources. Live migration facilitates high availability, fault management, load

level system maintenance. Since live migration is performed on the fly, it results


LIVE MIGRATION USING PRE-COPY APPROACH

This section discusses the idea behind pre-copy approach for live migration. During live


ource host to the destination host while the VM is still running on the source host. The frequently

updated pages, known as dirty pages are re-copied. The recopying of dirtied pages is continued till the

copied pages is not less than page dirtying rate. When the rate of re-copied pages is less than


] to compresses memory before migration is used to lessen migration time.

applications is analyzed in [13]. The

] under different levels of resource availability. Two

oblivious models were designed based on workload analysis at hypervisor level to predict

ates the cost of live migration based on performance

] allocates resources to virtual machines



used on the source host is freed.

Offline migration’s Total Migration Time(TMT) and Downtime(DT) for different


duration equal to the total migration time and the total migration time

. This section discusses the performance

ration dictates that the currently running VM be suspended and this suspended


image is resumed on the destination host and the memory the VM used on the source host is freed. On



acilitates high availability, fault management, load

level system maintenance. Since live migration is performed on the fly, it results


copy approach for live migration. During live


ource host to the destination host while the VM is still running on the source host. The frequently

copied. The recopying of dirtied pages is continued till the

copied pages is less than



page dirty rate, the VM in source host is stopped and the remaining dirtied pages are copied to the

destination host. The VM is resumed at the destination host. The difference in time when the VM on

the source host stops and VM at the destination host resumes is called downtime. The steps involved

in live migration of VMs using pre-copy approach are detailed below.

Step1: Preparation

Initially, a request is issued to migrate a VM from the source host to

confirming the availability of resources. Once the availability of resources at destination host is

confirmed, a VM of required size is reserved. If the required resources are not found at the

destination host, the VM simply continues to run on the source host unaffected. In the first iteration,

all pages are transferred from the source host to the destination host. The pages that are transferred

initially is called as the working set. Successive iterations copy only the dirtied

working set. The VM at the source host is suspended and the network traffic is redirected to the

destination host. At the end of this stage, there is a consistent suspended copy of the VM at both the

source host and the destination host. T

and is resumed in case of failure.

Step2: Migration After receiving a consistent OS image from the source host, a handshaking takes place

between the destination and the source hosts, the

responder. The source host discards the original VM and the destination host becomes the primary

host. The logical steps that are followed during the preparation and migration are summarized in

Figure 5.

During pre-migration process, the destination host is examined for availability of resources.

Once the resource availability is confirmed, the required resource for VM is reserved at the

destination host. Preparation includes pre

for resource availability to run the VM. In reservation stage, the resources for the new incoming VM

are reserved at the destination host. Then the source VM is stopped and dirty pages are copied to the

destination host. Migration is committed when the destination host’s VM is synchronized with VM

running at the source host. Once the destination host receives the consistent copy of the VM running

at the source host, the VM at source host is stopped and the VM at the destination hos

Figure 5: Time line diagram for pre



86



e source host stops and VM at the destination host resumes is called downtime. The steps involved

copy approach are detailed below.

Initially, a request is issued to migrate a VM from the source host to the destination host after



ntinues to run on the source host unaffected. In the first iteration,


initially is called as the working set. Successive iterations copy only the dirtied



source host and the destination host. The copy at the source host is still considered to be the primary

After receiving a consistent OS image from the source host, a handshaking takes place

between the destination and the source hosts, the destination being the initiator and source the



migration process, the destination host is examined for availability of resources.


destination host. Preparation includes pre-migration process where the destination host is examined



is committed when the destination host’s VM is synchronized with VM


at the source host, the VM at source host is stopped and the VM at the destination hos

Time line diagram for pre-copy approach




e source host stops and VM at the destination host resumes is called downtime. The steps involved

the destination host after



ntinues to run on the source host unaffected. In the first iteration,


initially is called as the working set. Successive iterations copy only the dirtied pages from the



he copy at the source host is still considered to be the primary

After receiving a consistent OS image from the source host, a handshaking takes place

destination being the initiator and source the



migration process, the destination host is examined for availability of resources.


tination host is examined



is committed when the destination host’s VM is synchronized with VM


at the source host, the VM at source host is stopped and the VM at the destination host is activated.



V. EXPERIMENTAL ANALYSIS

This section discusses the empirical analysis on performance of applications during offline

and live migration, addresses the impacts of different parameters that affect the offline and live

migration performance using pre- copy approach on xen virtualizat

• DOWNTIME

Figure 6

The downtime in offline migration is more compared to live migration as illustrated in Figure

6. This is due to the fact that the services provided by the VM in offline migration are suspended f

an interim duration equal to the total migration time. However in pre copy migration it is suspended

only in the final iteration. The reduction in amount of service downtime is achieved using live

migration.

The downtime in offline migration increases w

is equal to total migration time. In live migration, downtime may or may not increase with increase

in VM’s size, but depends on the rate at which memory pages are dirtied. Figure 6 shows the

downtime for live and offline migration which indicates that in offline migration downtime increases

with VM size, but in live migration it may or may not.

• TOTAL MIGRATION TIME

The total migration time in offline migration depends only on the size of VM but in live

migration total migration time depends on the size of VM and application behaviour as shown in

Figure 7. The total migration time in live migration is at least equal to total migration time of offline

migration.

Figure 7

0

10

20

30

40

50

60

70D

ow

n t

ime

in s

ec



87

ANALYSIS OF OFFLINE AND LIVE MIGRATION



copy approach on xen virtualization platform.

Figure 6: Offline vs live downtime


6. This is due to the fact that the services provided by the VM in offline migration are suspended f



The downtime in offline migration increases with increase in size of VM since the downtime



and offline migration which indicates that in offline migration downtime increases

with VM size, but in live migration it may or may not.

TOTAL MIGRATION TIME


on total migration time depends on the size of VM and application behaviour as shown in


Figure 7: Offline vs live total migration time

512 1024 2048

LIVE

OFFLINE

Memory in MB





6. This is due to the fact that the services provided by the VM in offline migration are suspended for



ith increase in size of VM since the downtime



and offline migration which indicates that in offline migration downtime increases


on total migration time depends on the size of VM and application behaviour as shown in




• PERFORMANCE OF APPLICATIONS

The performance of applications during live migration is better than offline migration as

shown in Figure 8. This is due to the fact that service downtime in live migration is lower than in

offline migration.

Figure 8

VI. PERFORMANCE ANALYSIS OF LIVE MIGRATION

• MEMORY VS DOWNTIME

As shown in Figure 9 the downtime is not directly proportional to the size of VM, but it also

depends on the application behaviour. That is, the downtime depends on the ra

pages are dirtied, apart from the size.

Figure 9

• CPU VS DOWNTIME

Figure 10 illustrates that the increase in CPU will not change the downtime; it can be

concluded that the change in amount of computational resources

downtime.

Figure 10: TMT and DT of VM vs Computational resource

0

5000

10000

15000

20000

Pe

rfo

rma

nce

0

50

100

150

Tim

e in

se

c



88

PERFORMANCE OF APPLICATIONS



Figure 8: Performance of application

PERFORMANCE ANALYSIS OF LIVE MIGRATION

MEMORY VS DOWNTIME


depends on the application behaviour. That is, the downtime depends on the rate at which memory

pages are dirtied, apart from the size.

Figure 9: Memory vs downtime


concluded that the change in amount of computational resources does not have any impact on the

TMT and DT of VM vs Computational resource

7-ZIP

COMPRESSION

(MIPS)

RAMspeed

(MB/sec)

(Integer)

PyBench

(milliseconds)

Cache Bench

(MB/s)

Witout migWith migOFFLINE

Applications

32 31

32 31

32 32

Openssl postGreSQL

2048 MB

1024 MB

512 MB

Applications





te at which memory


does not have any impact on the



• CPU VS TOTAL MIGRATION TIME

Figure 11

Computational resource has no impact on total migration time and downtime assuming that

there are sufficient computational resources available to initiate live migration.

demonstrates that the total migration time does not depend on the computati

instead, depends on the size of the memory. As we can see even when computational resources are

added by keeping memory resources constant the total migration time remains nearly constant.

• MEMORY VS TOTAL MIGRATION TIME

Memory resource has an impact on total migration time. As shown in Figure 12, as and when

there is an increase in size of VM, the total migration time also increases. Increase in cap value will

not alter the total migration time.

Figure 12: Memory vs total migrtaion with

• APPLICATION’S PERFORMANCE WITH AND WITHOUT MIGRATION

There is a performance degradation of an application when it is migrated. The amount of

degradation differs with different application. As shown in Figure 13 the Openssl application shows

lower performance degradation compared to any other application.

0

50

100

150

200

250

0

Mig

rati

on

tim

e-se

c



89

CPU VS TOTAL MIGRATION TIME

Figure 11: Total migration time vs resources


there are sufficient computational resources available to initiate live migration.

demonstrates that the total migration time does not depend on the computational resources and



MEMORY VS TOTAL MIGRATION TIME

as an impact on total migration time. As shown in Figure 12, as and when


Memory vs total migrtaion with varying CPU resources

APPLICATION’S PERFORMANCE WITH AND WITHOUT MIGRATION



lower performance degradation compared to any other application.

25 50 75 100 125 150 175 200

VCPU=1,RAM=1GB

VCPU=2,RAM=1GB

VCPU=1,RAM=2GB

VCPU=2,RAM=2GB

VCPU=1,RAM=512MB

VCPU=2,RAM=512MB

Cap Value in %



there are sufficient computational resources available to initiate live migration. Figure 11

onal resources and



as an impact on total migration time. As shown in Figure 12, as and when


varying CPU resources

APPLICATION’S PERFORMANCE WITH AND WITHOUT MIGRATION





90

Figure 13: Performance of applications with and without migration

• TOTAL MIGRATION TIME—BASE LINE CASE WITH APPLICATION

The previous attempts conclude that the total migration time is directly proportional to the

size of the VM. These analyses have some loopholes. For example, applications like Openssl and

RAMspeed each occupy VM of size 512 MB but the total migration time is 49 and 206 respectively.

From this it can be concluded that the total migration time not only depends on the size of VM but

also on application behaviour.

Figure 14: TMT in offline and live migration

Figure 14 shows the comparison of total migration time of live and offline migration. The

minimum time the live migration takes to migrate a VM is equivalent to the time taken to migrate the

same VM using offline migration.

• TOTAL TRANSFERRED DATA VS APPLICATIONS

The amount of data transferred during migration may not be directly proportional to the size

of the VM but it also depends on the nature of the application. The size of VM serving applications 1

and 3 is 512 MB while size of VM serving application 4 is 2 GB. From Figure 15 it can be concluded

that the total transferred data for application 1and 3 is more than the application 4. This indicates that

the size of the VM is not the only factor to decide the total transferred data, but also depends on the

nature of the application.

0

50

100

150

200

250

OPENSSL

(signal per

second)

PostgreSQL

(Transactions

per second)

Loopback TCP

Performance

(sec)

Parallel BZIP

Compression

(sec)

Threaded I/O

Tester (MB/s)

Witout mig With mig

Pe

rfo

rma

nce

Applications

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9

live TMT

offline TMT

Mig

rati

on

tim

e i

n s

ec

Applications



Figure 15: Migrated data in offline and live migration

VII. DISCUSSION AND CONCLUSIONS

This section discusses about the findings drawn from experimental analysis. The previous

attempts show that the memory size influences downtime and migration time. They also discuss that

total migration time and downtime increase with increase in VM size.

fail(have not been able) to compare the amount of data transferred during migrating a VM.

The analysis of previous work conclude the following

o Memory resource has an impact on total migration time and total migration time increases

increase in memory.

o Memory resource has an impact on downtime and downtime increases with increase in

memory.

o Total migration time depends on link bandwidth.

The current work has been able to derive the following:

o Computational resource has no impact

o Computational resource has no impact on downtime.

o Nature of the application influences downtime, total migration time and amount of data

transferred during live migration.

o The total migration time in offline migration is analysed

migration time for live migration.

o The performance degradation of an application during migration also depends on the nature of

the application. All applications do not exhibit the same level of degradation.

o Downtime depends on memory size and application behaviour

This paper discussed the performance analysis of offline and live migration techniques. The

offline and live migration techniques using precopy is analyzed for various parameters like total

migration time, downtime, application’s performance during migration and amount of data

transferred. It illustrates that the performance degradation during migration is dependent on type of

the application. In offline migration amount of data transferred during migration

of the VM but in live migration the amount of data transferred during migration depends on the

nature of the application.



91

Migrated data in offline and live migration

DISCUSSION AND CONCLUSIONS



total migration time and downtime increase with increase in VM size. The previous attempts


The analysis of previous work conclude the following

Memory resource has an impact on total migration time and total migration time increases

Memory resource has an impact on downtime and downtime increases with increase in

Total migration time depends on link bandwidth.

The current work has been able to derive the following:

Computational resource has no impact on total migration time.

Computational resource has no impact on downtime.

Nature of the application influences downtime, total migration time and amount of data

transferred during live migration.

The total migration time in offline migration is analysed and this would be the minimum total

migration time for live migration.

The performance degradation of an application during migration also depends on the nature of

the application. All applications do not exhibit the same level of degradation.

depends on memory size and application behaviour



downtime, application’s performance during migration and amount of data


the application. In offline migration amount of data transferred during migration depends on the size





The previous attempts


Memory resource has an impact on total migration time and total migration time increases with

Memory resource has an impact on downtime and downtime increases with increase in

Nature of the application influences downtime, total migration time and amount of data

and this would be the minimum total

The performance degradation of an application during migration also depends on the nature of



downtime, application’s performance during migration and amount of data


depends on the size




92

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