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Computer Engineering and Intelligent Systems www.iiste.org
ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online)
Vol.5, No.3, 2014
110
A Survey on Live Virtual Machine Migrations and its Techniques
Swapnil M. Parikh
Department of Computer Science and Engineering, Babaria Institute of Technology,
BITS edu Campus, Varnama, Vadodara, Gujarat, India – 391240
swapnil.parikh@gmail.com
Abstract
Today’s world is internet world. Almost all the people uses internet for accessing different services. In Cloud
Computing various cloud consumers demand variety of services as per their dynamically changing needs over
the internet. So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But
due to the availability of finite resources it is very difficult for cloud providers to provide all the demanded
services in time. From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So,
it’s a vital issue to meet cloud consumers’ QoS requirements and satisfaction. Virtualization mainly abstracts the
resources like CPU and Memory through Virtual Machine for efficient resource utilization. Virtual Machine
Migration is one of the key technique for dynamic resource management in cloud computing. This paper mainly
addresses key performance issues, challenges and techniques for live virtual machine migration in cloud
computing. It also focuses on the key issues related to these existing live virtual machine migration techniques
and summarizes them.
Keywords: Cloud Computing, Migration, Virtualization, Virtual Machine, Physical Machine, Resource
Management, Live Virtual Machine Migration.
1. Introduction
Because of the advancement in Information and Communication Technology (ICT) over past few years,
Computing has been considered as a utility like water, electricity, gas and telephony. These utilities are available
at any time to the consumers based on their requirement. Consumers pay service providers based on their usage
[1] [2] [3] [4].
Like all the other existing utilities, Computing utility is the basic computing service that meets the day to day
needs of the general community. To deliver this vision, a number of computing paradigms have been proposed,
of which the latest one is known as Cloud Computing. Cloud is nothing but large pool of easily accessible and
usable virtual resources [2] [3] [4] [5].
Dr. Rajkumar Buyya says “A Cloud is a type of parallel and distributed system consisting of a collection of
inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified
computing resource(s) based on service-level agreements established through negotiation between the service
provider and consumers.” [3]
In cloud computing various cloud consumers demand variety of services as per their dynamically changing needs.
So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But due to the
availability of finite resources it is very difficult for cloud providers to provide all the demanded services in time.
From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So, it’s a vital issue to
meet cloud consumers’ QoS requirements and satisfaction. The ultimate goal of efficient resource utilization in
cloud computing is to maximize the profit for cloud providers and to minimize the cost for cloud consumers.
Traditional resource allocation techniques are not adequate for cloud computing as it is based on virtualization
technology with distributed nature. Cloud computing introduces new challenges for manageable and flexible
resource allocation due to heterogeneity in hardware capabilities, workload estimation and characteristics in
order to meet Service Level Objectives of the cloud consumers’ applications.
Virtualization itself can be one of the solutions to provide resources to the cloud consumers efficiently by
running multiple VMs on top of single physical host. The term “virtualization” refers to the sharing of same
physical host across multiple concurrently running OS instances. Virtualization mainly abstracts the resources
like CPU and Memory through Virtual Machine for efficient resource utilization [8][14]. Virtualization
multiplexes computing resources on a single cloud platform.
Virtual Machine has been a research topic since past few years as it is independent of hardware implementation
and configurations. Migration is the process of transferring VM from one physical host to another physical host.
If the same can be achieved without interrupting its execution then it is said to be “live”. Live Virtual Machine
Computer Engineering and Intelligent Systems www.iiste.org
ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online)
Vol.5, No.3, 2014
111
Migration is one of the key technique for dynamic resource management in cloud computing [8][14].
The rest of the paper is organized as follows: Section II discusses various live virtual machine migration
techniques proposed by researchers’. Section III gives summary of all these live virtual machine migration
techniques with their used tools and possible improvements. Section IV presents conclusion and discussion on
live virtual machine migration techniques.
2. Literature Survey and Related Work
Sujesha Sudevalayam and Purushottam Kulkarni [9] argued that network affinity-awareness is required in
resource provisioning for virtual machines. Authors have quantified their work of benchmarking of link network
usage for both Xen and KVM virtualization technologies. Authors have also focused on building affinity-aware
models that can predict expected CPU resource requirements based on its location relative to its communicating
set of virtual machines – upon colocation and dispersion of virtual machines.
Pablo Graubner, Matthias Schmidt and Bernd Freisleben [10] presented a novel approach to virtual machine
consolidation based on energy efficient storage migration and live virtual machine migration. Authors tried to
save energy through virtual machine consolidation in IaaS cloud computing environment. Authors have
implemented the same approach using Eucalyptus which is an open source clone of the Amazon Elastic Compute
Cloud (Amazon EC2).
Tiago C. Ferreto, Marco A. S. Netto, Rodrigo N. Calheiros and Cesar A.F. De Rose [11] a new approach
named Dynamic Consolidation with Migration Control. Authors have discussed that current techniques like
static consolidation and dynamic consolidation doesn’t consider the steady usage of virtual machines. Due to
which problems may arise like migration cost and penalty to physical server. So, Authors claimed that for steady
usage migration can be avoided but for variable usage migration can be performed. Authors had used Linear
Programming Formulation and Heuristics approach for the same. Authors had evaluated their proposed approach
with TU-Berlin Workload and Google Workload.
Mayank Mishra, Anwesha Das, Purushottam Kulkarni and Anirudha Sahoo [12] discussed that live virtual
machine migration plays a vital role in dynamic resource management of cloud computing. Authors mainly
focused on efficient resource utilization in non peak periods to minimize wastage of resources. In order to
achieve goals like server consolidation, load balancing and hotspot mitigation, authors discussed three
components – when to migrate, which VM to migrate and where to migrate – and approaches followed by
different heuristics to apply migration techniques. Authors also discussed virtual machine migration over LAN
and WAN with their challenges.
Haikum Liu, Hai Jin, Xiaotei Liao, Chen Yu and Cheng-Zhong Xu [13] had designed, implemented and
evaluated a novel approach that minimises virtual machine migration downtime and network traffic. Authors had
adopted check pointing/recovery and trace/reply technologies for the same and implemented a transparent virtual
machine checkpoint with copy-on-write (COW) mechanism. Authors claimed that their proposed method can be
used in both LAN and WAN. The experimental results showed that a novel approach gives better performance.
Kejiang Ye, Xiaohong Jiang, Dawei Huang, Jianhai Chen and Bei Wang [14] proposed resource reservation
based live migration framework of multiple virtual machines. The target machine in the framework holds four
virtual machines: Migration Decision Maker, Migration Controller, Resource Reservation Controller and
Resource Monitor. Authors focused on improving the migration efficiency through live migration of virtual
machines and proposed three optimization methods: optimization in the source machine, parallel migration of
multiple virtual machines and workload-aware migration strategy. To improve the migration efficiency authors
had considered parameters like downtime, total migration time and workload performance overheads. Authors
claimed that resource reservation strategy is required at source machine and target machine.
Febio Checconi, Tomasso Cucunotta and Manuel Stein [15] addressed real time issues in Live Virtual
Machine Migration. Authors had presented a technique for live migration of real time applications. The main
factor that had been considered by authors is down time of virtual machines due to live migration. Also authors
have introduced probabilistic model for migration process to find out new set of migration policies by building a
sound mathematical theory. Deeper evaluation of the fully implemented proposed technique is still has to be
done by the authors.
3. Summary on Live Virtual Machine Migration Techniques
Table 1 summarizes the work done by various researchers and future work and/or gaps in their existing work.
Computer Engineering and Intelligent Systems www.iiste.org
ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online)
Vol.5, No.3, 2014
112
Table 1 Summary on Live Virtual Machine Migration Techniques
Year Author Techniques/Algorithms
Tools and/or
workload
used
Future work and/or gaps in existing
technologies
2013
Sujesha Sudevalayam and
Purushottam Kulkarni [9]
Affinity aware modelling
of CPU usage with
communicating VMs
Xen and
KVM
Heterogeneity of PMs are not
considered. Benchmarking of 100
Mbps link network usage is done (1
Gbps – not done)
2013
Pablo Graubner, Matthias
Schmidt and Bernd
Freisleben [10]
VM consolidation through
energy efficient storage
migration and live VM
migration
Eucalyptus
Resource management at higher layer
and overhead VM live migrations.
Year Author Techniques/Algorithms
Tools and/or
workload
used
Future work and/or gaps in existing
technologies
2011
Tiago C. Ferreto, Marco A.
S. Netto, Rodrigo N.
Calheiros and Cesar A.F.
De Rose [11]
Dynamic Server
Consolidation with
Migration Control
TU-Berlin
and Google
Workload
Can easily be implemented on
VMWare and Citrix Tools.
2012
Mayank Mishra, Anwesha
Das, Purushottam Kulkarni
and Anirudha Sahoo [12]
Live Virtual Machine
Migration
Not
Mentioned
Only load on the virtual machine for
migration is considered. Consumer
requirements and priority of job is not
considered.
2011
Haikum Liu, Hai Jin,
Xiaotei Liao, Chen Yu and
Cheng-Zhong Xu [13]
Virtual Machine
Checkpoint with copy-on-
write mechanism.
On LAN and
WAN
Multiprocessor virtual machine
migration and design a hybrid scheme
that can apply heuristics to choose
alternative algorithm between precopy
and proposed method.
2011
Kejiang Ye, Xiaohong
Jiang, Dawei Huang,
Jianhai Chen and Bei
Wang [14]
Live Migration of Virtual
Machines
Xen and
VMWare
Intelligent live migration machine can
be future work.
2009
Febio Checconi, Tomasso
Cucunotta and Manuel
Stein [15]
Real Time Issues in Live
Virtual Machine Migration
(new set of migration
policies)
KVM
Deeper evaluation of the fully
implemented proposed technique is
still has to be done by the authors.
4. Conclusion and Discussion
Cloud Computing is the new era of computing for delivering computing as a resource over the today’s internet
world. The success and beauty behind cloud computing is due to the cloud services provided with the cloud over
the internet. Due to the availability of finite resources, it is very important for cloud providers to manage and
assign all the resources in time to cloud consumers as their requirements are changing dynamically.
Live Virtual Machine Migration is one of the key notions for efficient dynamic resource management. Many
authors have proposed algorithms and methods for Live Virtual Machine Migration. In summary, all the authors
tried to achieve very low and predictable downtimes. They also tried to avail resources to the cloud consumers
during migration process.
References
[1] Peter Mell, Timothy Grance, “The NIST Definition of Cloud Computing (Draft)” in Computer Security
Division, Information Technology Laboratory, 2011.
[2] Swapnil M Parikh, “A Study on Cloud Computing and its Avenues” in National Conference on
Emerging Trends in Information Technology in association with World Journal of Science and
Technology 2013, Vol 3, No 3: 37-65.
[3] Swapnil M Parikh, “A Survey on Cloud Computing Resource Allocation Techniques” in 4th
Nirma
University International Conference on Engineering, 978-1-4673-1719-1/12, November 2013.
[4] Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz, Andy Konwinski,
Gunho Lee, David Patterson, Ariel Rabkin, Ion Stoica, and Matei Zaharia, “A View of Cloud
Computing (Draft)” in Communications of the ACM 2010, Vol 53, No 4.
[5] Rajkumar Buyya, Chee Shin Yeo, Srikumar Venugopala, James Broberg, Ivona Brandic, “Cloud
computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th
utility” in ELSEVIER - Future Generation Computer Systems 25 pg 599-616, 2009.
Computer Engineering and Intelligent Systems www.iiste.org
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Vol.5, No.3, 2014
113
[6] V. Krishna Reddy, B. Thirumala Rao, Dr. L.S.S. Reddy, P. Sai Kiran, “Research Issues in Cloud
Computing” in Global Journal of Computer Science and Technology 2011 Volume 11 Issue 11 Version
1.0 Online ISSN: 0975-4172 & Print ISSN: 0975-4350.
[7] Shufen Zhang, Hongcan Yan, Xuebin Chen, “Research on Key Technologies of Cloud Computing” in
ELSEVIER - International Conference on Medical Physics and Biomedical Engineering, Physics
Procedia 33 (2012) Pg No: 1791 – 1797.
[8] T.Mahiba and Jayashree, “Live Virtual Machine Migration in Dynamic Resource Management of
Virtualized Cloud Systems” in International Journal of Latest Trends in Engineering and Technology,
Vol 2 Issue 4 July 2013, ISSN: 2278-621X.
[9] Sujesha Sudevalayam and Purushottam Kulkarni, “Affinity-aware modelling of CPU usage with
communicating virtual machines” in Journal of Systems and Softwares 86 (2013) 2627-2638.
[10]Pablo Graubner, Matthias Schmidt and Bernd Freisleben, “Energy-Efficient Virtual Machine
Consolidation” in IEEE Computer Society, IT Pro, March/April 2013.
[11]Tiago C. Ferreto, Marco A. S. Netto, Rodrigo N. Calheiros and Cesar A.F. De Rose, “Server
Consolidation with migration control for virtualized data centers” in Future Generation Computer
Systems 27 (2011) 1027-1034.
[12]Mayank Mishra, Anwesha Das, Purushottam Kulkarni and Anirudha Sahoo, “Dynamic Resource
Management using Virtual Machine Migrations” in IEEE Communication Magazine (Cloud
Computing: Networking and Communication Challenges), September 2012.
[13]Haikum Liu, Hai Jin, Xiaotei Liao, Chen Yu and Cheng-Zhong Xu, “Live Virtual Machine Migration
via Asynchronous Replication and State Synchronisation” in IEEE Transactions on Parallel and
Distributed Systems, VOL 22, NO 12, December 2011.
[14]Kejiang Ye, Xiaohong Jiang, Dawei Huang, Jianhai Chen and Bei Wang, “Live Migration of Multiple
Virtual Machines with Resource Reservation in Cloud Computing Environments” in IEEE 4th
International Conference on Cloud Computing, 978-0-7695-4460-1, 2011.
[15]Febio Checconi, Tomasso Cucunotta and Manuel Stein, “Real Time Issues in Live Migration of Virtual
Machines” in Euro-Par'09 Proceedings of the 2009 international conference on Parallel processing
(ACM Digital Library), Pages 454-466.
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A survey on live virtual machine migrations and its techniques

  • 1. Computer Engineering and Intelligent Systems www.iiste.org ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online) Vol.5, No.3, 2014 110 A Survey on Live Virtual Machine Migrations and its Techniques Swapnil M. Parikh Department of Computer Science and Engineering, Babaria Institute of Technology, BITS edu Campus, Varnama, Vadodara, Gujarat, India – 391240 swapnil.parikh@gmail.com Abstract Today’s world is internet world. Almost all the people uses internet for accessing different services. In Cloud Computing various cloud consumers demand variety of services as per their dynamically changing needs over the internet. So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But due to the availability of finite resources it is very difficult for cloud providers to provide all the demanded services in time. From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So, it’s a vital issue to meet cloud consumers’ QoS requirements and satisfaction. Virtualization mainly abstracts the resources like CPU and Memory through Virtual Machine for efficient resource utilization. Virtual Machine Migration is one of the key technique for dynamic resource management in cloud computing. This paper mainly addresses key performance issues, challenges and techniques for live virtual machine migration in cloud computing. It also focuses on the key issues related to these existing live virtual machine migration techniques and summarizes them. Keywords: Cloud Computing, Migration, Virtualization, Virtual Machine, Physical Machine, Resource Management, Live Virtual Machine Migration. 1. Introduction Because of the advancement in Information and Communication Technology (ICT) over past few years, Computing has been considered as a utility like water, electricity, gas and telephony. These utilities are available at any time to the consumers based on their requirement. Consumers pay service providers based on their usage [1] [2] [3] [4]. Like all the other existing utilities, Computing utility is the basic computing service that meets the day to day needs of the general community. To deliver this vision, a number of computing paradigms have been proposed, of which the latest one is known as Cloud Computing. Cloud is nothing but large pool of easily accessible and usable virtual resources [2] [3] [4] [5]. Dr. Rajkumar Buyya says “A Cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resource(s) based on service-level agreements established through negotiation between the service provider and consumers.” [3] In cloud computing various cloud consumers demand variety of services as per their dynamically changing needs. So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But due to the availability of finite resources it is very difficult for cloud providers to provide all the demanded services in time. From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So, it’s a vital issue to meet cloud consumers’ QoS requirements and satisfaction. The ultimate goal of efficient resource utilization in cloud computing is to maximize the profit for cloud providers and to minimize the cost for cloud consumers. Traditional resource allocation techniques are not adequate for cloud computing as it is based on virtualization technology with distributed nature. Cloud computing introduces new challenges for manageable and flexible resource allocation due to heterogeneity in hardware capabilities, workload estimation and characteristics in order to meet Service Level Objectives of the cloud consumers’ applications. Virtualization itself can be one of the solutions to provide resources to the cloud consumers efficiently by running multiple VMs on top of single physical host. The term “virtualization” refers to the sharing of same physical host across multiple concurrently running OS instances. Virtualization mainly abstracts the resources like CPU and Memory through Virtual Machine for efficient resource utilization [8][14]. Virtualization multiplexes computing resources on a single cloud platform. Virtual Machine has been a research topic since past few years as it is independent of hardware implementation and configurations. Migration is the process of transferring VM from one physical host to another physical host. If the same can be achieved without interrupting its execution then it is said to be “live”. Live Virtual Machine
  • 2. Computer Engineering and Intelligent Systems www.iiste.org ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online) Vol.5, No.3, 2014 111 Migration is one of the key technique for dynamic resource management in cloud computing [8][14]. The rest of the paper is organized as follows: Section II discusses various live virtual machine migration techniques proposed by researchers’. Section III gives summary of all these live virtual machine migration techniques with their used tools and possible improvements. Section IV presents conclusion and discussion on live virtual machine migration techniques. 2. Literature Survey and Related Work Sujesha Sudevalayam and Purushottam Kulkarni [9] argued that network affinity-awareness is required in resource provisioning for virtual machines. Authors have quantified their work of benchmarking of link network usage for both Xen and KVM virtualization technologies. Authors have also focused on building affinity-aware models that can predict expected CPU resource requirements based on its location relative to its communicating set of virtual machines – upon colocation and dispersion of virtual machines. Pablo Graubner, Matthias Schmidt and Bernd Freisleben [10] presented a novel approach to virtual machine consolidation based on energy efficient storage migration and live virtual machine migration. Authors tried to save energy through virtual machine consolidation in IaaS cloud computing environment. Authors have implemented the same approach using Eucalyptus which is an open source clone of the Amazon Elastic Compute Cloud (Amazon EC2). Tiago C. Ferreto, Marco A. S. Netto, Rodrigo N. Calheiros and Cesar A.F. De Rose [11] a new approach named Dynamic Consolidation with Migration Control. Authors have discussed that current techniques like static consolidation and dynamic consolidation doesn’t consider the steady usage of virtual machines. Due to which problems may arise like migration cost and penalty to physical server. So, Authors claimed that for steady usage migration can be avoided but for variable usage migration can be performed. Authors had used Linear Programming Formulation and Heuristics approach for the same. Authors had evaluated their proposed approach with TU-Berlin Workload and Google Workload. Mayank Mishra, Anwesha Das, Purushottam Kulkarni and Anirudha Sahoo [12] discussed that live virtual machine migration plays a vital role in dynamic resource management of cloud computing. Authors mainly focused on efficient resource utilization in non peak periods to minimize wastage of resources. In order to achieve goals like server consolidation, load balancing and hotspot mitigation, authors discussed three components – when to migrate, which VM to migrate and where to migrate – and approaches followed by different heuristics to apply migration techniques. Authors also discussed virtual machine migration over LAN and WAN with their challenges. Haikum Liu, Hai Jin, Xiaotei Liao, Chen Yu and Cheng-Zhong Xu [13] had designed, implemented and evaluated a novel approach that minimises virtual machine migration downtime and network traffic. Authors had adopted check pointing/recovery and trace/reply technologies for the same and implemented a transparent virtual machine checkpoint with copy-on-write (COW) mechanism. Authors claimed that their proposed method can be used in both LAN and WAN. The experimental results showed that a novel approach gives better performance. Kejiang Ye, Xiaohong Jiang, Dawei Huang, Jianhai Chen and Bei Wang [14] proposed resource reservation based live migration framework of multiple virtual machines. The target machine in the framework holds four virtual machines: Migration Decision Maker, Migration Controller, Resource Reservation Controller and Resource Monitor. Authors focused on improving the migration efficiency through live migration of virtual machines and proposed three optimization methods: optimization in the source machine, parallel migration of multiple virtual machines and workload-aware migration strategy. To improve the migration efficiency authors had considered parameters like downtime, total migration time and workload performance overheads. Authors claimed that resource reservation strategy is required at source machine and target machine. Febio Checconi, Tomasso Cucunotta and Manuel Stein [15] addressed real time issues in Live Virtual Machine Migration. Authors had presented a technique for live migration of real time applications. The main factor that had been considered by authors is down time of virtual machines due to live migration. Also authors have introduced probabilistic model for migration process to find out new set of migration policies by building a sound mathematical theory. Deeper evaluation of the fully implemented proposed technique is still has to be done by the authors. 3. Summary on Live Virtual Machine Migration Techniques Table 1 summarizes the work done by various researchers and future work and/or gaps in their existing work.
  • 3. Computer Engineering and Intelligent Systems www.iiste.org ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online) Vol.5, No.3, 2014 112 Table 1 Summary on Live Virtual Machine Migration Techniques Year Author Techniques/Algorithms Tools and/or workload used Future work and/or gaps in existing technologies 2013 Sujesha Sudevalayam and Purushottam Kulkarni [9] Affinity aware modelling of CPU usage with communicating VMs Xen and KVM Heterogeneity of PMs are not considered. Benchmarking of 100 Mbps link network usage is done (1 Gbps – not done) 2013 Pablo Graubner, Matthias Schmidt and Bernd Freisleben [10] VM consolidation through energy efficient storage migration and live VM migration Eucalyptus Resource management at higher layer and overhead VM live migrations. Year Author Techniques/Algorithms Tools and/or workload used Future work and/or gaps in existing technologies 2011 Tiago C. Ferreto, Marco A. S. Netto, Rodrigo N. Calheiros and Cesar A.F. De Rose [11] Dynamic Server Consolidation with Migration Control TU-Berlin and Google Workload Can easily be implemented on VMWare and Citrix Tools. 2012 Mayank Mishra, Anwesha Das, Purushottam Kulkarni and Anirudha Sahoo [12] Live Virtual Machine Migration Not Mentioned Only load on the virtual machine for migration is considered. Consumer requirements and priority of job is not considered. 2011 Haikum Liu, Hai Jin, Xiaotei Liao, Chen Yu and Cheng-Zhong Xu [13] Virtual Machine Checkpoint with copy-on- write mechanism. On LAN and WAN Multiprocessor virtual machine migration and design a hybrid scheme that can apply heuristics to choose alternative algorithm between precopy and proposed method. 2011 Kejiang Ye, Xiaohong Jiang, Dawei Huang, Jianhai Chen and Bei Wang [14] Live Migration of Virtual Machines Xen and VMWare Intelligent live migration machine can be future work. 2009 Febio Checconi, Tomasso Cucunotta and Manuel Stein [15] Real Time Issues in Live Virtual Machine Migration (new set of migration policies) KVM Deeper evaluation of the fully implemented proposed technique is still has to be done by the authors. 4. Conclusion and Discussion Cloud Computing is the new era of computing for delivering computing as a resource over the today’s internet world. The success and beauty behind cloud computing is due to the cloud services provided with the cloud over the internet. Due to the availability of finite resources, it is very important for cloud providers to manage and assign all the resources in time to cloud consumers as their requirements are changing dynamically. Live Virtual Machine Migration is one of the key notions for efficient dynamic resource management. Many authors have proposed algorithms and methods for Live Virtual Machine Migration. In summary, all the authors tried to achieve very low and predictable downtimes. They also tried to avail resources to the cloud consumers during migration process. References [1] Peter Mell, Timothy Grance, “The NIST Definition of Cloud Computing (Draft)” in Computer Security Division, Information Technology Laboratory, 2011. [2] Swapnil M Parikh, “A Study on Cloud Computing and its Avenues” in National Conference on Emerging Trends in Information Technology in association with World Journal of Science and Technology 2013, Vol 3, No 3: 37-65. [3] Swapnil M Parikh, “A Survey on Cloud Computing Resource Allocation Techniques” in 4th Nirma University International Conference on Engineering, 978-1-4673-1719-1/12, November 2013. [4] Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz, Andy Konwinski, Gunho Lee, David Patterson, Ariel Rabkin, Ion Stoica, and Matei Zaharia, “A View of Cloud Computing (Draft)” in Communications of the ACM 2010, Vol 53, No 4. [5] Rajkumar Buyya, Chee Shin Yeo, Srikumar Venugopala, James Broberg, Ivona Brandic, “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility” in ELSEVIER - Future Generation Computer Systems 25 pg 599-616, 2009.
  • 4. Computer Engineering and Intelligent Systems www.iiste.org ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online) Vol.5, No.3, 2014 113 [6] V. Krishna Reddy, B. Thirumala Rao, Dr. L.S.S. Reddy, P. Sai Kiran, “Research Issues in Cloud Computing” in Global Journal of Computer Science and Technology 2011 Volume 11 Issue 11 Version 1.0 Online ISSN: 0975-4172 & Print ISSN: 0975-4350. [7] Shufen Zhang, Hongcan Yan, Xuebin Chen, “Research on Key Technologies of Cloud Computing” in ELSEVIER - International Conference on Medical Physics and Biomedical Engineering, Physics Procedia 33 (2012) Pg No: 1791 – 1797. [8] T.Mahiba and Jayashree, “Live Virtual Machine Migration in Dynamic Resource Management of Virtualized Cloud Systems” in International Journal of Latest Trends in Engineering and Technology, Vol 2 Issue 4 July 2013, ISSN: 2278-621X. [9] Sujesha Sudevalayam and Purushottam Kulkarni, “Affinity-aware modelling of CPU usage with communicating virtual machines” in Journal of Systems and Softwares 86 (2013) 2627-2638. [10]Pablo Graubner, Matthias Schmidt and Bernd Freisleben, “Energy-Efficient Virtual Machine Consolidation” in IEEE Computer Society, IT Pro, March/April 2013. [11]Tiago C. Ferreto, Marco A. S. Netto, Rodrigo N. Calheiros and Cesar A.F. De Rose, “Server Consolidation with migration control for virtualized data centers” in Future Generation Computer Systems 27 (2011) 1027-1034. [12]Mayank Mishra, Anwesha Das, Purushottam Kulkarni and Anirudha Sahoo, “Dynamic Resource Management using Virtual Machine Migrations” in IEEE Communication Magazine (Cloud Computing: Networking and Communication Challenges), September 2012. [13]Haikum Liu, Hai Jin, Xiaotei Liao, Chen Yu and Cheng-Zhong Xu, “Live Virtual Machine Migration via Asynchronous Replication and State Synchronisation” in IEEE Transactions on Parallel and Distributed Systems, VOL 22, NO 12, December 2011. [14]Kejiang Ye, Xiaohong Jiang, Dawei Huang, Jianhai Chen and Bei Wang, “Live Migration of Multiple Virtual Machines with Resource Reservation in Cloud Computing Environments” in IEEE 4th International Conference on Cloud Computing, 978-0-7695-4460-1, 2011. [15]Febio Checconi, Tomasso Cucunotta and Manuel Stein, “Real Time Issues in Live Migration of Virtual Machines” in Euro-Par'09 Proceedings of the 2009 international conference on Parallel processing (ACM Digital Library), Pages 454-466.