SlideShare a Scribd company logo
1 of 6
Download to read offline
KNOWLEDGECUDDLE PUBLICATION
International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1
1
www.knowledgecuddle.com
Process migration and load balancing.
Drashti Patel
drashtipatel6576@yahoo.in
Gujarat Technological University,
Gujarat, India.
ABSTRACT: Process migration is the act of transferring an active process between two machines Today in the real world
while process is under execution it may happens so that the process gets stacked in between. If this happens for more than
one process then there should be some mechanism that helps process to precede further .Here comes the IDEA of LOAD
BALANCING using PROCESS MIGRATION and restoring the process from the point it left off on the selected destination
node. Several implementations have been built for different operating systems. With increasing deployment of distributed
systems in general, process migration is again receiving more attention in both research and product development. We use
process migration to control over the load sharing, availability of long process, utilizing some special resources.
Keywords: Immigrant, Migrant, Refugee, Sparsely.
I. INTRODUCTION.
It may happens so that the process gets Today in the real while process is under execution stacked in between.
 If this happens for more than one process then there should be some mechanism that helps process to proceed further.
 Here comes the IDEA of LOAD BALANCING using PROCESS MIGRATION.
MIGRATION TERMINOLOGY: Process migration is the act of transferring process between two machines in which one is
source and other is destination during its execution. Some architecture also defines a host or home node, which is the node
where the process logically runs. Transferred state includes the process’s address space, execution point, communication state
and other operating system dependent state. Task migration represents transferring a task between two machines during
execution of its threads. Remote invocation is the creation of a process on remote node. Remote invocation is usually a less
“expensive” operation than process migration. Passive data represents traditional means of transferring data between
computers; it has been employed ever since the first two computers were connected. Active data can be further classified into
mobile code, process migration and mobile agents. These three classes represent incremental evolution of state transfer.
Mobile code, such as Java applets, transfers only code between nodes.
II. ALGORITHM
A. EAGER COPY
The eager (all) strategy copies all of the address space at the migration time. Initial costs may be in the range of minutes.
Checkpoint/restart implementations typically use this strategy, such as Condor or LSF. eager (dirty) strategy can be deployed
if there is remote paging support. This is a variant of the eager(all) strategy that transfers only modified (dirty) pages.
Unmodified pages are paged in on request from a backing store. Eager (dirty) significantly reduces the initial transfer costs
when a process has a large address space. Systems supporting eager (dirty) strategy include MOSIX.
B. copy of reference
The COR strategy has the lowest initial costs, ranging from a few tens to a few hundred microseconds. However, it increases
the run-time costs, and it also requires substantial changes to the underlying operating system and to the paging support. It is
KNOWLEDGECUDDLE PUBLICATION
International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1
2
www.knowledgecuddle.com
strategy is a network version of demand paging: pages are transferred only upon reference. While dirty pages are brought from
the source node, clean pages can be brought either from the source node or from the backing store.
C. Flushing
The flushing strategy consists of flushing dirty pages to disk and then accessing them on demand from disk instead of from
memory on the source node as in copy on- reference [Douglas and Ousterhout [3]]. The flushing strategy is like the eager
(dirty) transfer strategy from the perspective of the source, and like copy on- reference from the target’s viewpoint. It leaves
dependencies on the server, but not on the source node.
D. Pre Copy
The pre copy strategy reduces the “freeze” time of the process, the time that process is neither executed on the source nor on
the destination node. While the process is executed on the source node, the address space is being transferred to the remote
node until the number of dirty pages is smaller than a fixed limit. Pages dirtied during pre copy have to be copied a second
time.
FIGURE: 1 PROCCESS MIGRATION
KNOWLEDGECUDDLE PUBLICATION
International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1
3
www.knowledgecuddle.com
KNOWLEDGECUDDLE PUBLICATION
International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1
4
www.knowledgecuddle.com
III. Process migration enables
 Dynamic load distribution, by migrating processes
 From overloaded nodes to less loaded ones,
 Fault resilience, by migrating processes from nodes
 That may have experienced a partial failure,
 Improved system administration, by migrating
 Processes from the nodes that are about to be shut down or otherwise made unavailable, and
 Data access locality, by migrating processes closer to the source of some data.
IV. FUTURE
The goals of process migration are closely tied with the type of applications that use migration, as described in next section.
The goals of process migration include:
KNOWLEDGECUDDLE PUBLICATION
International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1
5
www.knowledgecuddle.com
Accessing more processing power is a goal of migration when it is used for load distribution. Migration is particularly
important in the receiver-initiated distributed scheduling algorithms, where a lightly loaded node announces its availability and
initiates process migration from an overloaded node.
Exploitation of resource locality is a goal of migration in cases when it is more efficient to access resources locally than
remotely. Moving a process to another end of a communication channel transforms remote communication to local and thereby
significantly improves performance. It is also possible that the resource is not remotely accessible.
Resource sharing is enabled by migration to a specific node with a special hardware device, large amounts of free memory, or
some other unique resource. e.g. NOW for utilizing memory of remote node.
Fault resilience is improved by migration from a partially failed node, or in the case of long-running applications when
failures of different kinds (network, devices) are probable [Chu et al., 1980]. In this context, migration can be used in
combination with check pointing, such as in Condor.
System admonition is simplified if long-running computations can be temporarily transferred to other machines. For example,
an application could migrate from a node that will be shutdown, and then migrate back after the node is brought back up.
Another example is the repartitioning of large machines.
V. CONCLUSION
So, by transferring any process from one host or home node to another node we can use resources, memory and give CPU
time equally. So we use process migration to control over the load sharing, availability of long process, utilizing some special
resources.
REFERENCES
[1]. Dannenberg, R. B. and Hibbard, P. G. (July 1985). A Butler Process for Resource Sharing on a Spice Machine. IEEE
Transactions on Office Information Systems, 3(3):234–252.
[2]. Hwang, K., Croft, W., Wahl, B., Briggs, F., Simons, W., and Coates, C. (April 1982). A UNIX-Based Local Computer
Network with Load Balancing. IEEE Computer.
[3]. Klein rock, L. (1976). Queue Systems vol. 2: Computer Applications. Willey, New York.
[4]. Hildebrand, D. (April 1992). An Architectural Overview of QNX. Proceedings of the USENIX Workshop on Micro-Kernels
and Other Kernel Architectures, pages 113–126
[5]. OMG (March 1996). Common Object Request Broker Architecture and Specification. Object Management Group
Document Number 96.03.04
[6]. Shapiro, M., Dickman, P., and Plainfossé, D. (August 1992). Robust, Distributed References and Acyclic Garbage
Collection.
[7]. Proceedings of the Symposium on Principles of Distributed Computing, pages 135-146.
[8]. Shapiro, M., Gautron, P., and Mosseri, L. (July 1989). Persistence and Migration for C++ Objects. Proceedings of the
ECOOP 1989–European Conference on Object-Oriented Programming.
KNOWLEDGECUDDLE PUBLICATION
International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1
6
www.knowledgecuddle.com
[9]. Shivaratri, N. G. and Krueger, P. (May-June 1990). Two Adaptive Location Policies for Global Scheduling Algorithms.
Proceedings of the 10th International Conference on Distributed Computing Systems, pages 502–509

More Related Content

What's hot

Dominant resource fairness fair allocation of multiple resource types
Dominant resource fairness fair allocation of multiple resource typesDominant resource fairness fair allocation of multiple resource types
Dominant resource fairness fair allocation of multiple resource typesanet18
 
QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...
QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...
QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...Papitha Velumani
 
Efficient load rebalancing for distributed file system in Clouds
Efficient load rebalancing for distributed file system in CloudsEfficient load rebalancing for distributed file system in Clouds
Efficient load rebalancing for distributed file system in CloudsIJERA Editor
 
Dynamic Resource Allocation Algorithm using Containers
Dynamic Resource Allocation Algorithm using ContainersDynamic Resource Allocation Algorithm using Containers
Dynamic Resource Allocation Algorithm using ContainersIRJET Journal
 
Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...
Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...
Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...Frederic Desprez
 
Presentation southernstork 2009-nov-southernworkshop
Presentation southernstork 2009-nov-southernworkshopPresentation southernstork 2009-nov-southernworkshop
Presentation southernstork 2009-nov-southernworkshopbalmanme
 
Survey on cloud backup services of personal storage
Survey on cloud backup services of personal storageSurvey on cloud backup services of personal storage
Survey on cloud backup services of personal storageeSAT Journals
 
A Brief on MapReduce Performance
A Brief on MapReduce PerformanceA Brief on MapReduce Performance
A Brief on MapReduce PerformanceAM Publications
 
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...IJSRD
 
An experimental evaluation of performance
An experimental evaluation of performanceAn experimental evaluation of performance
An experimental evaluation of performanceijcsa
 
Dynamic Cloud Partitioning and Load Balancing in Cloud
Dynamic Cloud Partitioning and Load Balancing in Cloud Dynamic Cloud Partitioning and Load Balancing in Cloud
Dynamic Cloud Partitioning and Load Balancing in Cloud Shyam Hajare
 

What's hot (20)

ICICCE0298
ICICCE0298ICICCE0298
ICICCE0298
 
Dominant resource fairness fair allocation of multiple resource types
Dominant resource fairness fair allocation of multiple resource typesDominant resource fairness fair allocation of multiple resource types
Dominant resource fairness fair allocation of multiple resource types
 
4 026
4 0264 026
4 026
 
QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...
QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...
QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing...
 
Efficient load rebalancing for distributed file system in Clouds
Efficient load rebalancing for distributed file system in CloudsEfficient load rebalancing for distributed file system in Clouds
Efficient load rebalancing for distributed file system in Clouds
 
Resource management
Resource managementResource management
Resource management
 
Dynamic Resource Allocation Algorithm using Containers
Dynamic Resource Allocation Algorithm using ContainersDynamic Resource Allocation Algorithm using Containers
Dynamic Resource Allocation Algorithm using Containers
 
H04502048051
H04502048051H04502048051
H04502048051
 
Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...
Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...
Grid'5000: Running a Large Instrument for Parallel and Distributed Computing ...
 
Presentation southernstork 2009-nov-southernworkshop
Presentation southernstork 2009-nov-southernworkshopPresentation southernstork 2009-nov-southernworkshop
Presentation southernstork 2009-nov-southernworkshop
 
cloud schedualing
cloud schedualingcloud schedualing
cloud schedualing
 
Survey on cloud backup services of personal storage
Survey on cloud backup services of personal storageSurvey on cloud backup services of personal storage
Survey on cloud backup services of personal storage
 
A Brief on MapReduce Performance
A Brief on MapReduce PerformanceA Brief on MapReduce Performance
A Brief on MapReduce Performance
 
GRID COMPUTING
GRID COMPUTINGGRID COMPUTING
GRID COMPUTING
 
Scheduling in cloud
Scheduling in cloudScheduling in cloud
Scheduling in cloud
 
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
 
[IJET V2I2P18] Authors: Roopa G Yeklaspur, Dr.Yerriswamy.T
[IJET V2I2P18] Authors: Roopa G Yeklaspur, Dr.Yerriswamy.T[IJET V2I2P18] Authors: Roopa G Yeklaspur, Dr.Yerriswamy.T
[IJET V2I2P18] Authors: Roopa G Yeklaspur, Dr.Yerriswamy.T
 
An experimental evaluation of performance
An experimental evaluation of performanceAn experimental evaluation of performance
An experimental evaluation of performance
 
Dynamic Cloud Partitioning and Load Balancing in Cloud
Dynamic Cloud Partitioning and Load Balancing in Cloud Dynamic Cloud Partitioning and Load Balancing in Cloud
Dynamic Cloud Partitioning and Load Balancing in Cloud
 
Optimize Virtual Machine Placement in Banker Algorithm for Energy Efficient C...
Optimize Virtual Machine Placement in Banker Algorithm for Energy Efficient C...Optimize Virtual Machine Placement in Banker Algorithm for Energy Efficient C...
Optimize Virtual Machine Placement in Banker Algorithm for Energy Efficient C...
 

Viewers also liked

Understanding Reasonable Accommodation
Understanding Reasonable AccommodationUnderstanding Reasonable Accommodation
Understanding Reasonable AccommodationCurley & Rothman, LLC
 
Valdez multimedia project
Valdez multimedia projectValdez multimedia project
Valdez multimedia projectmellie1218
 
Luật hình sự Việt Nam - Pháp luật đại cương
Luật hình sự Việt Nam - Pháp luật đại cươngLuật hình sự Việt Nam - Pháp luật đại cương
Luật hình sự Việt Nam - Pháp luật đại cươngMyLan2014
 
Confident with the Principle, Critical with the Practice: Kenyans Speak Out ...
Confident with the Principle, Critical with the Practice:  Kenyans Speak Out ...Confident with the Principle, Critical with the Practice:  Kenyans Speak Out ...
Confident with the Principle, Critical with the Practice: Kenyans Speak Out ...Ipsos
 
Are You a Victim of Sexual Harassment in the Workplace?
Are You a Victim of Sexual Harassment in the Workplace?Are You a Victim of Sexual Harassment in the Workplace?
Are You a Victim of Sexual Harassment in the Workplace?Curley & Rothman, LLC
 
As revision 99 qs
As revision 99 qsAs revision 99 qs
As revision 99 qsronniekueh
 
Family Coaching as Early Help for Whole Families
Family Coaching as Early Help for Whole FamiliesFamily Coaching as Early Help for Whole Families
Family Coaching as Early Help for Whole FamiliesBASPCAN
 
Vedran Puclin-Diploma_Eng
Vedran Puclin-Diploma_EngVedran Puclin-Diploma_Eng
Vedran Puclin-Diploma_EngVedran Puclin
 
Customer relation manager perfomance appraisal 2
Customer relation manager perfomance appraisal 2Customer relation manager perfomance appraisal 2
Customer relation manager perfomance appraisal 2tonychoper5704
 
How effective is the combination of your main product and ancillary tasks?
How effective is the combination of your main product and ancillary tasks?How effective is the combination of your main product and ancillary tasks?
How effective is the combination of your main product and ancillary tasks?Jake Wilde
 
Vedran puclin diploma eng
Vedran puclin diploma engVedran puclin diploma eng
Vedran puclin diploma engVedran Puclin
 

Viewers also liked (17)

Top 7 CSR
Top 7 CSRTop 7 CSR
Top 7 CSR
 
Understanding Reasonable Accommodation
Understanding Reasonable AccommodationUnderstanding Reasonable Accommodation
Understanding Reasonable Accommodation
 
Valdez multimedia project
Valdez multimedia projectValdez multimedia project
Valdez multimedia project
 
Luật hình sự Việt Nam - Pháp luật đại cương
Luật hình sự Việt Nam - Pháp luật đại cươngLuật hình sự Việt Nam - Pháp luật đại cương
Luật hình sự Việt Nam - Pháp luật đại cương
 
Amali
AmaliAmali
Amali
 
Confident with the Principle, Critical with the Practice: Kenyans Speak Out ...
Confident with the Principle, Critical with the Practice:  Kenyans Speak Out ...Confident with the Principle, Critical with the Practice:  Kenyans Speak Out ...
Confident with the Principle, Critical with the Practice: Kenyans Speak Out ...
 
Patti
PattiPatti
Patti
 
Are You a Victim of Sexual Harassment in the Workplace?
Are You a Victim of Sexual Harassment in the Workplace?Are You a Victim of Sexual Harassment in the Workplace?
Are You a Victim of Sexual Harassment in the Workplace?
 
Tipanna
TipannaTipanna
Tipanna
 
As revision 99 qs
As revision 99 qsAs revision 99 qs
As revision 99 qs
 
Consulting – LyteSpark
Consulting – LyteSparkConsulting – LyteSpark
Consulting – LyteSpark
 
Family Coaching as Early Help for Whole Families
Family Coaching as Early Help for Whole FamiliesFamily Coaching as Early Help for Whole Families
Family Coaching as Early Help for Whole Families
 
Vedran Puclin-Diploma_Eng
Vedran Puclin-Diploma_EngVedran Puclin-Diploma_Eng
Vedran Puclin-Diploma_Eng
 
Customer relation manager perfomance appraisal 2
Customer relation manager perfomance appraisal 2Customer relation manager perfomance appraisal 2
Customer relation manager perfomance appraisal 2
 
How effective is the combination of your main product and ancillary tasks?
How effective is the combination of your main product and ancillary tasks?How effective is the combination of your main product and ancillary tasks?
How effective is the combination of your main product and ancillary tasks?
 
Vedran puclin diploma eng
Vedran puclin diploma engVedran puclin diploma eng
Vedran puclin diploma eng
 
Health
HealthHealth
Health
 

Similar to Process migration and load balancing

Final jaypaper linux
Final jaypaper linuxFinal jaypaper linux
Final jaypaper linuxjaya380
 
Virtual Machine Migration Techniques in Cloud Environment: A Survey
Virtual Machine Migration Techniques in Cloud Environment: A SurveyVirtual Machine Migration Techniques in Cloud Environment: A Survey
Virtual Machine Migration Techniques in Cloud Environment: A Surveyijsrd.com
 
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMCLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMijcseit
 
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMCLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMijcseit
 
Implementation of Agent Based Dynamic Distributed Service
Implementation of Agent Based Dynamic Distributed ServiceImplementation of Agent Based Dynamic Distributed Service
Implementation of Agent Based Dynamic Distributed ServiceCSCJournals
 
5. the grid implementing production grid
5. the grid implementing production grid5. the grid implementing production grid
5. the grid implementing production gridDr Sandeep Kumar Poonia
 
Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...
Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...
Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...IJCSIS Research Publications
 
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...IJERA Editor
 
A Novel Approach for Workload Optimization and Improving Security in Cloud Co...
A Novel Approach for Workload Optimization and Improving Security in Cloud Co...A Novel Approach for Workload Optimization and Improving Security in Cloud Co...
A Novel Approach for Workload Optimization and Improving Security in Cloud Co...IOSR Journals
 
Cloud computing – partitioning algorithm
Cloud computing – partitioning algorithmCloud computing – partitioning algorithm
Cloud computing – partitioning algorithmijcseit
 
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...IJSRD
 
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...IJSRD
 
Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...
Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...
Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...AM Publications
 
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...IOSR Journals
 

Similar to Process migration and load balancing (20)

Final jaypaper linux
Final jaypaper linuxFinal jaypaper linux
Final jaypaper linux
 
Virtual Machine Migration Techniques in Cloud Environment: A Survey
Virtual Machine Migration Techniques in Cloud Environment: A SurveyVirtual Machine Migration Techniques in Cloud Environment: A Survey
Virtual Machine Migration Techniques in Cloud Environment: A Survey
 
Grid Computing
Grid ComputingGrid Computing
Grid Computing
 
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMCLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
 
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMCLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHM
 
Implementation of Agent Based Dynamic Distributed Service
Implementation of Agent Based Dynamic Distributed ServiceImplementation of Agent Based Dynamic Distributed Service
Implementation of Agent Based Dynamic Distributed Service
 
Rep on grid computing
Rep on grid computingRep on grid computing
Rep on grid computing
 
5. the grid implementing production grid
5. the grid implementing production grid5. the grid implementing production grid
5. the grid implementing production grid
 
Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...
Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...
Improve the Offloading Decision by Adaptive Partitioning of Task for Mobile C...
 
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...
Technical Review on Live Virtual Machine Migration Techniques for Eucalyptus ...
 
A01260104
A01260104A01260104
A01260104
 
D017212027
D017212027D017212027
D017212027
 
A Novel Approach for Workload Optimization and Improving Security in Cloud Co...
A Novel Approach for Workload Optimization and Improving Security in Cloud Co...A Novel Approach for Workload Optimization and Improving Security in Cloud Co...
A Novel Approach for Workload Optimization and Improving Security in Cloud Co...
 
Cloud computing – partitioning algorithm
Cloud computing – partitioning algorithmCloud computing – partitioning algorithm
Cloud computing – partitioning algorithm
 
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
 
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...
 
Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...
Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...
Improved Utilization of Infrastructure of Clouds by using Upgraded Functional...
 
H017144148
H017144148H017144148
H017144148
 
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
 
[IJET V2I5P18] Authors:Pooja Mangla, Dr. Sandip Kumar Goyal
[IJET V2I5P18] Authors:Pooja Mangla, Dr. Sandip Kumar Goyal[IJET V2I5P18] Authors:Pooja Mangla, Dr. Sandip Kumar Goyal
[IJET V2I5P18] Authors:Pooja Mangla, Dr. Sandip Kumar Goyal
 

Recently uploaded

What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxwendy cai
 
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...ranjana rawat
 
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escortsranjana rawat
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 
Introduction to Multiple Access Protocol.pptx
Introduction to Multiple Access Protocol.pptxIntroduction to Multiple Access Protocol.pptx
Introduction to Multiple Access Protocol.pptxupamatechverse
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxpranjaldaimarysona
 
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...Dr.Costas Sachpazis
 
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...ranjana rawat
 
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile serviceCall Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile servicerehmti665
 
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxIntroduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxupamatechverse
 
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxDecoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxJoão Esperancinha
 
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur EscortsCall Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur High Profile
 
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSAPPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSKurinjimalarL3
 
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...ranjana rawat
 
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learningmisbanausheenparvam
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSCAESB
 
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escortsranjana rawat
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVRajaP95
 

Recently uploaded (20)

9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
 
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptx
 
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
 
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 
Introduction to Multiple Access Protocol.pptx
Introduction to Multiple Access Protocol.pptxIntroduction to Multiple Access Protocol.pptx
Introduction to Multiple Access Protocol.pptx
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptx
 
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
 
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
 
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile serviceCall Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile service
 
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxIntroduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptx
 
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxDecoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
 
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur EscortsCall Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
 
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSAPPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
 
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
 
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learning
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
 
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
 

Process migration and load balancing

  • 1. KNOWLEDGECUDDLE PUBLICATION International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1 1 www.knowledgecuddle.com Process migration and load balancing. Drashti Patel drashtipatel6576@yahoo.in Gujarat Technological University, Gujarat, India. ABSTRACT: Process migration is the act of transferring an active process between two machines Today in the real world while process is under execution it may happens so that the process gets stacked in between. If this happens for more than one process then there should be some mechanism that helps process to precede further .Here comes the IDEA of LOAD BALANCING using PROCESS MIGRATION and restoring the process from the point it left off on the selected destination node. Several implementations have been built for different operating systems. With increasing deployment of distributed systems in general, process migration is again receiving more attention in both research and product development. We use process migration to control over the load sharing, availability of long process, utilizing some special resources. Keywords: Immigrant, Migrant, Refugee, Sparsely. I. INTRODUCTION. It may happens so that the process gets Today in the real while process is under execution stacked in between.  If this happens for more than one process then there should be some mechanism that helps process to proceed further.  Here comes the IDEA of LOAD BALANCING using PROCESS MIGRATION. MIGRATION TERMINOLOGY: Process migration is the act of transferring process between two machines in which one is source and other is destination during its execution. Some architecture also defines a host or home node, which is the node where the process logically runs. Transferred state includes the process’s address space, execution point, communication state and other operating system dependent state. Task migration represents transferring a task between two machines during execution of its threads. Remote invocation is the creation of a process on remote node. Remote invocation is usually a less “expensive” operation than process migration. Passive data represents traditional means of transferring data between computers; it has been employed ever since the first two computers were connected. Active data can be further classified into mobile code, process migration and mobile agents. These three classes represent incremental evolution of state transfer. Mobile code, such as Java applets, transfers only code between nodes. II. ALGORITHM A. EAGER COPY The eager (all) strategy copies all of the address space at the migration time. Initial costs may be in the range of minutes. Checkpoint/restart implementations typically use this strategy, such as Condor or LSF. eager (dirty) strategy can be deployed if there is remote paging support. This is a variant of the eager(all) strategy that transfers only modified (dirty) pages. Unmodified pages are paged in on request from a backing store. Eager (dirty) significantly reduces the initial transfer costs when a process has a large address space. Systems supporting eager (dirty) strategy include MOSIX. B. copy of reference The COR strategy has the lowest initial costs, ranging from a few tens to a few hundred microseconds. However, it increases the run-time costs, and it also requires substantial changes to the underlying operating system and to the paging support. It is
  • 2. KNOWLEDGECUDDLE PUBLICATION International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1 2 www.knowledgecuddle.com strategy is a network version of demand paging: pages are transferred only upon reference. While dirty pages are brought from the source node, clean pages can be brought either from the source node or from the backing store. C. Flushing The flushing strategy consists of flushing dirty pages to disk and then accessing them on demand from disk instead of from memory on the source node as in copy on- reference [Douglas and Ousterhout [3]]. The flushing strategy is like the eager (dirty) transfer strategy from the perspective of the source, and like copy on- reference from the target’s viewpoint. It leaves dependencies on the server, but not on the source node. D. Pre Copy The pre copy strategy reduces the “freeze” time of the process, the time that process is neither executed on the source nor on the destination node. While the process is executed on the source node, the address space is being transferred to the remote node until the number of dirty pages is smaller than a fixed limit. Pages dirtied during pre copy have to be copied a second time. FIGURE: 1 PROCCESS MIGRATION
  • 3. KNOWLEDGECUDDLE PUBLICATION International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1 3 www.knowledgecuddle.com
  • 4. KNOWLEDGECUDDLE PUBLICATION International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1 4 www.knowledgecuddle.com III. Process migration enables  Dynamic load distribution, by migrating processes  From overloaded nodes to less loaded ones,  Fault resilience, by migrating processes from nodes  That may have experienced a partial failure,  Improved system administration, by migrating  Processes from the nodes that are about to be shut down or otherwise made unavailable, and  Data access locality, by migrating processes closer to the source of some data. IV. FUTURE The goals of process migration are closely tied with the type of applications that use migration, as described in next section. The goals of process migration include:
  • 5. KNOWLEDGECUDDLE PUBLICATION International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1 5 www.knowledgecuddle.com Accessing more processing power is a goal of migration when it is used for load distribution. Migration is particularly important in the receiver-initiated distributed scheduling algorithms, where a lightly loaded node announces its availability and initiates process migration from an overloaded node. Exploitation of resource locality is a goal of migration in cases when it is more efficient to access resources locally than remotely. Moving a process to another end of a communication channel transforms remote communication to local and thereby significantly improves performance. It is also possible that the resource is not remotely accessible. Resource sharing is enabled by migration to a specific node with a special hardware device, large amounts of free memory, or some other unique resource. e.g. NOW for utilizing memory of remote node. Fault resilience is improved by migration from a partially failed node, or in the case of long-running applications when failures of different kinds (network, devices) are probable [Chu et al., 1980]. In this context, migration can be used in combination with check pointing, such as in Condor. System admonition is simplified if long-running computations can be temporarily transferred to other machines. For example, an application could migrate from a node that will be shutdown, and then migrate back after the node is brought back up. Another example is the repartitioning of large machines. V. CONCLUSION So, by transferring any process from one host or home node to another node we can use resources, memory and give CPU time equally. So we use process migration to control over the load sharing, availability of long process, utilizing some special resources. REFERENCES [1]. Dannenberg, R. B. and Hibbard, P. G. (July 1985). A Butler Process for Resource Sharing on a Spice Machine. IEEE Transactions on Office Information Systems, 3(3):234–252. [2]. Hwang, K., Croft, W., Wahl, B., Briggs, F., Simons, W., and Coates, C. (April 1982). A UNIX-Based Local Computer Network with Load Balancing. IEEE Computer. [3]. Klein rock, L. (1976). Queue Systems vol. 2: Computer Applications. Willey, New York. [4]. Hildebrand, D. (April 1992). An Architectural Overview of QNX. Proceedings of the USENIX Workshop on Micro-Kernels and Other Kernel Architectures, pages 113–126 [5]. OMG (March 1996). Common Object Request Broker Architecture and Specification. Object Management Group Document Number 96.03.04 [6]. Shapiro, M., Dickman, P., and Plainfossé, D. (August 1992). Robust, Distributed References and Acyclic Garbage Collection. [7]. Proceedings of the Symposium on Principles of Distributed Computing, pages 135-146. [8]. Shapiro, M., Gautron, P., and Mosseri, L. (July 1989). Persistence and Migration for C++ Objects. Proceedings of the ECOOP 1989–European Conference on Object-Oriented Programming.
  • 6. KNOWLEDGECUDDLE PUBLICATION International Journal of Research in Advance Engineering (IJRAE) – Volume-1 Issue -1 6 www.knowledgecuddle.com [9]. Shivaratri, N. G. and Krueger, P. (May-June 1990). Two Adaptive Location Policies for Global Scheduling Algorithms. Proceedings of the 10th International Conference on Distributed Computing Systems, pages 502–509