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
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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
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] 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
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
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
70
Downtimeinsec
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
Performance
0
50
100
150
Timeinsec
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 mig
With mig
OFFLINE
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
Migrationtime-sec
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
Performance
Applications
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9
live TMT
offline TMT
Migrationtimeinsec
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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[16] Jason Sonnek, James Greensky, Robert Reutiman and Abhishek Chandra, Starling:
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[17] Dr. Narayan A. Joshi, “Load Balancing in Cloud using Process Migration”, International
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