International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Survey on Dynamic Resource Allocation Strategy in Cloud Computing EnvironmentEditor IJCATR
Cloud computing becomes quite popular among cloud users by offering a variety of resources. This is an on demand service because it offers dynamic flexible resource allocation and guaranteed services in pay as-you-use manner to public. In this paper, we present the several dynamic resource allocation techniques and its performance. This paper provides detailed description of the dynamic resource allocation technique in cloud for cloud users and comparative study provides the clear detail about the different techniques
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Survey on Dynamic Resource Allocation Strategy in Cloud Computing EnvironmentEditor IJCATR
Cloud computing becomes quite popular among cloud users by offering a variety of resources. This is an on demand service because it offers dynamic flexible resource allocation and guaranteed services in pay as-you-use manner to public. In this paper, we present the several dynamic resource allocation techniques and its performance. This paper provides detailed description of the dynamic resource allocation technique in cloud for cloud users and comparative study provides the clear detail about the different techniques
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
dynamic resource allocation using virtual machines for cloud computing enviro...Kumar Goud
Abstract—Cloud computing allows business customers to scale up and down their resource usage based on needs., we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of “skewness” to measure the unevenness in the multidimensional resource utilization of a server. By minimizing imbalance, we will mix completely different of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.
Index Terms—Cloud computing, resource management, virtualization, green computing.
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Enviro...SaikiranReddy Sama
In Dynamic Resource Allocation, WE PRESENT A SYSTEM THAT USES VIRTUALIZATION TECHNOLOGY TO ALLOCATE DATA CENTER RESOURCES DYNAMICALLY.
WE INTRODUCE THE CONCEPT OF “SKEWNESS”.
And BY MINIMIZING SKEWNESS, WE CAN COMBINE DIFFERENT TYPES OF WORKLOADS NICELY AND IMPROVE THE OVERALL UTILIZATION OF SERVER RESOURCES.
WE DEVELOP A SET OF HEURISTICS THAT PREVENT OVERLOAD IN THE SYSTEM EFFECTIVELY WHILE SAVING ENERGY USED.
Dynamic resource Allocation using Virtual Machines For Cloud Computing
Efficient Resource Allocation to Virtual Machine in Cloud Computing Using an ...ijceronline
The focus of the paper is to generate an advance algorithm of resource allocation and load balancing that can deduced and avoid the dead lock while allocating the processes to virtual machine. In VM while processes are allocate they executes in queue , the first process get resources , other remains in waiting state .As rest of VM remains idle . To utilize the resources, we have analyze the algorithm with the help of First-Come, First-Served (FCFS) Scheduling, Shortest-Job-First (SJR) Scheduling, Priority Scheduling, Round Robin (RR) and CloudSIM Simulator.
Dynamic Cloud Partitioning and Load Balancing in Cloud Shyam Hajare
Cloud computing is the emerging and transformational paradigm in the field of information technology. It mostly focuses in providing various services on demand and resource allocation and secure data storage are some of them. To store huge amount of data and accessing data from such metadata is new challenge. Distributing and balancing of the load over a cloud using cloud partitioning can ease the situation. Implementing load balancing by considering static as well as dynamic parameters can improve the performance cloud service provider and can improve the user satisfaction. Implementation the model can provide dynamic way of resource selection de-pending upon different situation of cloud environment at the time of accessing cloud provisions based on cloud partitioning. This model can provide effective load balancing algorithm over the cloud environment, better refresh time methods and better load status evaluation methods.
Load Balancing In Cloud Computing:A ReviewIOSR Journals
Abstract: As the IT industry is growing day by day, the need of computing and storage is increasing
rapidly. The amount of data exchanged over the network is constantly increasing. Thus the process of this
increasing mass of data requires more computer equipment to meet the various needs of the organizations.
To better capitalize their investment, the over-equipped organizations open their infrastructures to others by
exploiting the Internet and other important technologies such as virtualization by creating a new computing
model: the cloud computing. Cloud computing is one of the significant milestones in recent times in the
history of computers. The basic concept of cloud computing is to provide a platform for sharing of resources
which includes software and infrastructure with the help of virtualization. This paper presents a brief review
of cloud computing. The main emphasize of this paper is on the load balancing technique in cloud
computing.
Keywords: Cloud Computing, Load Balancing, Dynamic Load Balancing, Virtualization, Data Center.
AUTO RESOURCE MANAGEMENT TO ENHANCE RELIABILITY AND ENERGY CONSUMPTION IN HET...IJCNCJournal
A classic information processing has been replaced by cloud computing in more studies where cloud computing becomes more popular and growing than other computing models. Cloud computing works for providing on-demand services for users. Reliability and energy consumption are two hot challenges and tradeoffs problem in the cloud computing environment that requires accurate attention and research. This paper proposes an Auto Resource Management (ARM) scheme to enhance reliability by reducing the Service Level Agreement (SLA) violation and reduce energy consumed by cloud computing servers. In this context, the ARM consists of three compounds, they are static/dynamic threshold, virtual machine selection policy, and short prediction resource utilization method. The Minimum Utilization Non-Negative (MUN) virtual machine selection policy and Rate of Change (RoC) dynamic threshold present in this paper. Also, a method of choosing a value as the static threshold is proposed. To improve ARM performance, the paper proposes a Short Prediction Resource Utilization (SPRU) that aims to improve the process of decision making by including the resources utilization of future time and the current time. The output results show that SPRU enhanced the decision-making process for managing cloud computing resources and reduced energy consumption and the SLA violation. The proposed scheme tested under real workload data over the CloudSim simulator.
Role of Virtual Machine Live Migration in Cloud Load BalancingIOSR Journals
Abstract: Cloud computing has touched almost every field of the life. Hence number of cloud application
consumers is increasing every day and so as the number of application request to the cloud provider. This leads
increment of workload in many of the cloud nodes. The motive to use load balancing concepts in cloud
environment is to efficiently utilize available resources keeping in mind that no any single system is heavily
loaded or not a single system is idle during the active phase of the request completion. Even though cloud
computing being a software facility most often, how does it actually performs well in heavily loaded
environment at processor level, is discussed in the paper. This paper aims to throw some light on what is cloud
load balancing and what is the role of Virtual machine migration in improving it.
Keywords: Cloud load balancing, Live Migration, Migration, Virtualization, Virtual machine.
LIVE VIRTUAL MACHINE MIGRATION USING SHADOW PAGING IN CLOUD COMPUTINGcsandit
Cloud Computing shares computing resources to execute application. Cloud systems provide high-specification resources in the form of services, leading to the provision of user convenience and greater ease for personal-computer users; however, expansions of the cloudsystem service necessitate a corresponding enhancement of the technology that is used for server-resource management. In this paper, by monitoring the resources of a cloud server, we sought to identify the causes of server overload and degradation, followed by the running of a dynamic-page-migration mechanism. According to this process, we designed the proposed migration architecture for the minimization of user inconvenience
Load Balancing in Cloud Computing Environment: A Comparative Study of Service...Eswar Publications
Load balancing is a computer networking method to distribute workload across multiple computers or a computer cluster, network links, central processing units, disk drives, or other resources, to achieve optimal resource utilization, maximize throughput, minimize response time, and avoid overload. Using multiple components with load balancing, instead of a single component, may increase reliability through redundancy. The
load balancing service is usually provided by dedicated software or hardware, such as a multilayer switch or a Domain Name System server. In this paper, the existing static algorithms used for simple cloud load balancing have been identified and also a hybrid algorithm for developments in the future is suggested.
Today Cloud computing is used in a wide range of domains. By using cloud computing a user
can utilize services and pool of resources through internet. The cloud computing platform
guarantees subscribers that it will live up to the service level agreement (SLA) in providing
resources as service and as per needs. However, it is essential that the provider be able to
effectively manage the resources. One of the important roles of the cloud computing platform is
to balance the load amongst different servers in order to avoid overloading in any host and
improve resource utilization.
It is defined as a distributed system containing a collection of computing and communication
resources located in distributed data enters which are shared by several end users. It has widely
been adopted by the industry, though there are many existing issues like Load Balancing, Virtual
Machine Migration, Server Consolidation, Energy Management, etc.
Could the “C” in HPC stand for Cloud?This paper examines aspects of computing important in HPC (compute and network bandwidth, compute and network latency, memory size and bandwidth, I/O, and so on) and how they are affected by various virtualization technologies. For more information on IBM Systems, visit http://ibm.co/RKEeMO.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
www.irjes.com
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
dynamic resource allocation using virtual machines for cloud computing enviro...Kumar Goud
Abstract—Cloud computing allows business customers to scale up and down their resource usage based on needs., we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of “skewness” to measure the unevenness in the multidimensional resource utilization of a server. By minimizing imbalance, we will mix completely different of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.
Index Terms—Cloud computing, resource management, virtualization, green computing.
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Enviro...SaikiranReddy Sama
In Dynamic Resource Allocation, WE PRESENT A SYSTEM THAT USES VIRTUALIZATION TECHNOLOGY TO ALLOCATE DATA CENTER RESOURCES DYNAMICALLY.
WE INTRODUCE THE CONCEPT OF “SKEWNESS”.
And BY MINIMIZING SKEWNESS, WE CAN COMBINE DIFFERENT TYPES OF WORKLOADS NICELY AND IMPROVE THE OVERALL UTILIZATION OF SERVER RESOURCES.
WE DEVELOP A SET OF HEURISTICS THAT PREVENT OVERLOAD IN THE SYSTEM EFFECTIVELY WHILE SAVING ENERGY USED.
Dynamic resource Allocation using Virtual Machines For Cloud Computing
Efficient Resource Allocation to Virtual Machine in Cloud Computing Using an ...ijceronline
The focus of the paper is to generate an advance algorithm of resource allocation and load balancing that can deduced and avoid the dead lock while allocating the processes to virtual machine. In VM while processes are allocate they executes in queue , the first process get resources , other remains in waiting state .As rest of VM remains idle . To utilize the resources, we have analyze the algorithm with the help of First-Come, First-Served (FCFS) Scheduling, Shortest-Job-First (SJR) Scheduling, Priority Scheduling, Round Robin (RR) and CloudSIM Simulator.
Dynamic Cloud Partitioning and Load Balancing in Cloud Shyam Hajare
Cloud computing is the emerging and transformational paradigm in the field of information technology. It mostly focuses in providing various services on demand and resource allocation and secure data storage are some of them. To store huge amount of data and accessing data from such metadata is new challenge. Distributing and balancing of the load over a cloud using cloud partitioning can ease the situation. Implementing load balancing by considering static as well as dynamic parameters can improve the performance cloud service provider and can improve the user satisfaction. Implementation the model can provide dynamic way of resource selection de-pending upon different situation of cloud environment at the time of accessing cloud provisions based on cloud partitioning. This model can provide effective load balancing algorithm over the cloud environment, better refresh time methods and better load status evaluation methods.
Load Balancing In Cloud Computing:A ReviewIOSR Journals
Abstract: As the IT industry is growing day by day, the need of computing and storage is increasing
rapidly. The amount of data exchanged over the network is constantly increasing. Thus the process of this
increasing mass of data requires more computer equipment to meet the various needs of the organizations.
To better capitalize their investment, the over-equipped organizations open their infrastructures to others by
exploiting the Internet and other important technologies such as virtualization by creating a new computing
model: the cloud computing. Cloud computing is one of the significant milestones in recent times in the
history of computers. The basic concept of cloud computing is to provide a platform for sharing of resources
which includes software and infrastructure with the help of virtualization. This paper presents a brief review
of cloud computing. The main emphasize of this paper is on the load balancing technique in cloud
computing.
Keywords: Cloud Computing, Load Balancing, Dynamic Load Balancing, Virtualization, Data Center.
AUTO RESOURCE MANAGEMENT TO ENHANCE RELIABILITY AND ENERGY CONSUMPTION IN HET...IJCNCJournal
A classic information processing has been replaced by cloud computing in more studies where cloud computing becomes more popular and growing than other computing models. Cloud computing works for providing on-demand services for users. Reliability and energy consumption are two hot challenges and tradeoffs problem in the cloud computing environment that requires accurate attention and research. This paper proposes an Auto Resource Management (ARM) scheme to enhance reliability by reducing the Service Level Agreement (SLA) violation and reduce energy consumed by cloud computing servers. In this context, the ARM consists of three compounds, they are static/dynamic threshold, virtual machine selection policy, and short prediction resource utilization method. The Minimum Utilization Non-Negative (MUN) virtual machine selection policy and Rate of Change (RoC) dynamic threshold present in this paper. Also, a method of choosing a value as the static threshold is proposed. To improve ARM performance, the paper proposes a Short Prediction Resource Utilization (SPRU) that aims to improve the process of decision making by including the resources utilization of future time and the current time. The output results show that SPRU enhanced the decision-making process for managing cloud computing resources and reduced energy consumption and the SLA violation. The proposed scheme tested under real workload data over the CloudSim simulator.
Role of Virtual Machine Live Migration in Cloud Load BalancingIOSR Journals
Abstract: Cloud computing has touched almost every field of the life. Hence number of cloud application
consumers is increasing every day and so as the number of application request to the cloud provider. This leads
increment of workload in many of the cloud nodes. The motive to use load balancing concepts in cloud
environment is to efficiently utilize available resources keeping in mind that no any single system is heavily
loaded or not a single system is idle during the active phase of the request completion. Even though cloud
computing being a software facility most often, how does it actually performs well in heavily loaded
environment at processor level, is discussed in the paper. This paper aims to throw some light on what is cloud
load balancing and what is the role of Virtual machine migration in improving it.
Keywords: Cloud load balancing, Live Migration, Migration, Virtualization, Virtual machine.
LIVE VIRTUAL MACHINE MIGRATION USING SHADOW PAGING IN CLOUD COMPUTINGcsandit
Cloud Computing shares computing resources to execute application. Cloud systems provide high-specification resources in the form of services, leading to the provision of user convenience and greater ease for personal-computer users; however, expansions of the cloudsystem service necessitate a corresponding enhancement of the technology that is used for server-resource management. In this paper, by monitoring the resources of a cloud server, we sought to identify the causes of server overload and degradation, followed by the running of a dynamic-page-migration mechanism. According to this process, we designed the proposed migration architecture for the minimization of user inconvenience
Load Balancing in Cloud Computing Environment: A Comparative Study of Service...Eswar Publications
Load balancing is a computer networking method to distribute workload across multiple computers or a computer cluster, network links, central processing units, disk drives, or other resources, to achieve optimal resource utilization, maximize throughput, minimize response time, and avoid overload. Using multiple components with load balancing, instead of a single component, may increase reliability through redundancy. The
load balancing service is usually provided by dedicated software or hardware, such as a multilayer switch or a Domain Name System server. In this paper, the existing static algorithms used for simple cloud load balancing have been identified and also a hybrid algorithm for developments in the future is suggested.
Today Cloud computing is used in a wide range of domains. By using cloud computing a user
can utilize services and pool of resources through internet. The cloud computing platform
guarantees subscribers that it will live up to the service level agreement (SLA) in providing
resources as service and as per needs. However, it is essential that the provider be able to
effectively manage the resources. One of the important roles of the cloud computing platform is
to balance the load amongst different servers in order to avoid overloading in any host and
improve resource utilization.
It is defined as a distributed system containing a collection of computing and communication
resources located in distributed data enters which are shared by several end users. It has widely
been adopted by the industry, though there are many existing issues like Load Balancing, Virtual
Machine Migration, Server Consolidation, Energy Management, etc.
Could the “C” in HPC stand for Cloud?This paper examines aspects of computing important in HPC (compute and network bandwidth, compute and network latency, memory size and bandwidth, I/O, and so on) and how they are affected by various virtualization technologies. For more information on IBM Systems, visit http://ibm.co/RKEeMO.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
www.irjes.com
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
www.irjes.com
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
THRESHOLD BASED VM PLACEMENT TECHNIQUE FOR LOAD BALANCED RESOURCE PROVISIONIN...IJCNCJournal
The unbalancing load issue is a multi-variation, multi-imperative issue that corrupts the execution and productivity of processing assets. Workload adjusting methods give solutions of load unbalancing circumstances for two bothersome aspects over-burdening and under-stacking. Cloud computing utilizes planning and workload balancing for a virtualized environment, resource partaking in cloud foundation. These two factors must be handled in an improved way in cloud computing to accomplish ideal resource sharing. Henceforth, there requires productive resource, asset reservation for guaranteeing load advancement in the cloud. This work aims to present an incorporated resource, asset reservation, and workload adjusting calculation for effective cloud provisioning. The strategy develops a Priority-based Resource Scheduling Model to acquire the resource, asset reservation with threshold-based load balancing for improving the proficiency in cloud framework. Extending utilization of Virtual Machines through the suitable and sensible outstanding task at hand modifying is then practiced by intensely picking a job from submitting jobs using Priority-based Resource Scheduling Model to acquire resource asset reservation. Experimental evaluations represent, the proposed scheme gives better results by reducing execution time, with minimum resource cost and improved resource utilization in dynamic resource provisioning conditions.
DYNAMIC ALLOCATION METHOD FOR EFFICIENT LOAD BALANCING IN VIRTUAL MACHINES FO...acijjournal
This paper proposes a Dynamic resource allocation method for Cloud computing. Cloud computing is a model for delivering information technology services in which resources are retrieved from the internet through web-based tools and applications, rather than a direct connection to a server. Users can set up
and boot the required resources and they have to pay only for the required resources. Thus, in the future providing a mechanism for efficient resource management and assignment will be an important objective of Cloud computing. In this project we propose a method, dynamic scheduling and consolidation mechanism that allocate resources based on the load of Virtual Machines (VMs) on Infrastructure as a service (IaaS). This method enables users to dynamically add and/or delete one or more instances on the basis of the load and the conditions specified by the user. Our objective is to develop an effective load balancing algorithm using Virtual Machine Monitoring to
maximize or minimize different performance parameters(throughput for example) for the Clouds of
different sizes (virtual topology de-pending on the application requirement).
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Virtual Machine Migration and Allocation in Cloud Computing: A Reviewijtsrd
Cloud computing is an emerging computing technology that maintains computational resources on large data centers and accessed through internet, rather than on local computers. VM migration provides the capability to balance the load, system maintenance, etc. Virtualization technology gives power to cloud computing. The virtual machine migration techniques can be divided into two categories that is pre copy and post copy approach. The process to move running applications or VMs from one physical machine to another is known as VM migration. In migration process the processor state, storage, memory and network connection are moved from one host to another.. Two important performance metrics are downtime and total migration time that the users care about most, because these metrics deals with service degradation and the time during which the service is unavailable. This paper focus on the analysis of live VM migration Techniques in cloud computing. Khushbu Singh Chandel | Dr. Avinash Sharma "Virtual Machine Migration and Allocation in Cloud Computing: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29556.pdfPaper URL: https://www.ijtsrd.com/computer-science/computer-network/29556/virtual-machine-migration-and-allocation-in-cloud-computing-a-review/khushbu-singh-chandel
Resource Allocation using Virtual Machine Migration: A Surveyidescitation
As virtualization is proving to be dominant in
enterprise and organizational networks there is a need for
operators and administrators to pay more attention to live
migration of virtual machines (VMs) with the main objective
of workload balancing, monitoring, fault management, low-
level system maintenance and good performance with minimal
service downtimes. It is also a crucial aspect of cloud computing
that offers strategies to implement the dynamic allocation of
resources. Virtualization also enables virtual machine
migration to eliminate hotspots in data centers .However the
security associated with VMs live migration has not received
thorough analysis. Further, the negative impact on service
levels of running applications is likely to occur during the
live VM migration hence a better understanding of its
implications on the system performance is highly required.
In this survey we explore the security issues involved in live
migration of VMs and demonstrate the importance of security
during the migration process. A model which demonstrates
the cost incurred in reconfiguring a cloud-based environment
in response to the workload variations is studied. It is also
proved that migration cost is acceptable but should not be
neglected, particularly in systems where service availability
and response times are imposed by stringent Service Level
Agreements (SLAs). A system that provides automation of
monitoring and detection of hotspots and determination of
the new mapping of physical to virtual resources and finally
initiates the required migrations based on its observations is
also studied. These are experimented using Xen Virtual
Machine Manager. Migration based resource Managers for
virtualized environments are presented by comparing and
discussing several types of underlying algorithms from
algorithmistic issues point of view.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Adaptive Offloading in Mobile Cloud Computing by automatic partitioning approach of tasks is the idea to augment execution through migrating heavy computation from mobile devices to resourceful cloud servers and then receive the results from them via wireless networks. Offloading is an effective way to
overcome the resources and functionalities constraints
of the mobile devices since it can release them from
intensive processing and increase performance of the
mobile applications, in terms of response time.
Offloading brings many potential benefits, such as
energy saving, performance improvement, reliability
improvement, ease for the software developers and
better exploitation of contextual information.
Parameters about method transitions, response times,
cost and energy consumptions are dynamically reestimated
at runtime during application executions.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Virtualization Technology using Virtual Machines for Cloud ComputingIJMER
Cloud computing is the delivery of computing and storage capacity as a service to a community of end users. The name “cloud computing” comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts services with a user's software, data and computation over a network. End users access cloud-based applications through a web browser or mobile application or a light-weight desktop while the business software and user's data are stored on servers at a remote location. Proponents claim that cloud computing environment allows enterprises to get their applications up and running faster, with improved manageability and less maintenance, and enables IT industry to more rapidly adjust resources to meet fluctuating and unpredictable business demand. In this paper, we present a system that uses virtualization technology to allocate the data center resources dynamically based on the application demands and support green computing by optimizing the number of servers in use. This method multiplexes virtual to physical resources adaptively based on the changing demand. We use the concept of skewness metric to combine virtual machines with different resource characteristics appropriately so that the capacities of servers are well utilized.
ABSTRACT
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time
GROUP BASED RESOURCE MANAGEMENT AND PRICING MODEL IN CLOUD COMPUTINGijcsit
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time.
Cars are a very important part of this modern world because they give luxury and comfort. Even
though they are comfortable, some problems always keep arising on the safety side. After a lot of research they
rectified certain problems using air bags, auto parking, turbo charger, pedal shift…, etc.
And now we are going to discuss about one such problem that arises on the safety side. An unsuspected
accident occurs when people smash their fingers in between the car doors. Due to this kind of accident around
120,000 people are injured every year. But this was not taken as a very major safety concern for the customer.
To avoid this kind accident due to car doors, we are introducing “SAFETY DOOR LOCK SYSTEM”
with the help of “HYDRAULIC PISTON AND IR SENSORS”.
The major working process of the “SAFETY DOOR LOCK SYSTEM”is, when a person places his/her
hand or fingers in the gap between the door and the outer panel, at the time when the closing action of the door
takes place, the Sensors start to transmit the Infra Red Rays to the Receivers at the
other end, and so even if someone closes the door without anybody‟s knowledge the hydraulic piston will
automatically come out and stop the door from closing and prevent the person from the unsuspected accident
and minor injuries by the car door and ensure maximum safety to the customer.
Extrusion can be defined as the process of subjecting a material to compression so that it is forced to
flow through an opening of a die and takes the shape of the hole. Multi-hole extrusion is the process of
extruding the products through a die having more than one hole. Multi-hole extrusion increases the production
rate and reduces the cost of production. In this study the ram force has calculated experimentally for single hole
and multi-hole extrusion. The comparison of ram forces between the single hole and multi-hole extrusion
provides the inverse relation between the numbers of holes in a die and ram force. The experimental lengths of
the extruded products through the various holes of multi-hole die are different. It indicates that the flow pattern
is dependent on the material behavior. The micro-hardness test has done for the extruded products of lead
through multi-hole die. It is observed that the hardness of the extruded lead products from the central hole is
found to be more than that of the products extruded from other holes. The study suggests that multi-hole
extrusion can be used for obtaining the extruded products of lead with varying hardness. The micro-structure
study has done for the lead material before and after extrusion. It is observed that the size of grains of lead
material after extrusion is smaller than the original lead.
Analysis of Agile and Multi-Agent Based Process Scheduling Modelirjes
As an answer of long growing frustration of waterfall Software development life cycle concepts,
agile software development concept was evolved in 90’s. The most popular agile methodologies is the Extreme
Programming (XP). Most software companies nowadays aim to produce efficient, flexible and valuable
Software in short time period with minimal costs, and within unstable, changing environments. This complex
problem can be modeled as a multi-agent based system, where agents negotiate resources. Agents can be used to
represent projects and resources. Crucial for the multi-agent based system in project scheduling model, is the
availability of an effective algorithm for prioritizing and scheduling of task. To evaluate the models, simulations
were carried out with real life and several generated data sets. The developed model (Multi-agent based System)
provides an optimized and flexible agile process scheduling and reduces overheads in the software process as it
responds quickly to changing requirements without excessive work in project scheduling.
Effects of Cutting Tool Parameters on Surface Roughnessirjes
This paper presents of the influence on surface roughness of Co28Cr6Mo medical alloy machined
on a CNC lathe based on cutting parameters (rotational speed, feed rate, depth of cut and nose radius).The
influences of cutting parameters have been presented in graphical form for understanding. To achieve the
minimum surface roughness, the optimum values obtained for rpm, feed rate, depth of cut and nose radius were
respectively, 318 rpm, 0,1 mm/rev, 0,7 mm and 0,8 mm. Maximum surface roughness has been revealed the
values obtained for rpm, feed rate, depth of cut and nose radius were respectively, 318 rpm, 0,25 mm/rev, 0,9
mm and 0,4 mm.
Possible limits of accuracy in measurement of fundamental physical constantsirjes
The measurement uncertainties of Fundamental Physical Constants should take into account all
possible and most influencing factors. One from them is the finiteness of the model that causes the existence of
a-priori error. The proposed formula for calculation of this error provides a comparison of its value with the
actual experimental measurement error that cannot be done an arbitrarily small. According to the suggested
approach, the error of the researched Fundamental Physical Constant, measured in conventional field studies,
will always be higher than the error caused by the finite number of dimensional recorded variables of physicalmathematical
models. Examples of practical application of the considered concept for measurement of fine
structure constant, speed of light and Newtonian constant of gravitation are discussed.
Performance Comparison of Energy Detection Based Spectrum Sensing for Cogniti...irjes
With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing
demand for wireless radio spectrum. However, the policy of fixed spectrum assignment produces a bottleneck for more
efficient spectrum utilization, such that a great portion of the licensed spectrum is severely under-utilized. So the concept of
cognitive radio was introduced to address this issue.The inefficient usage of the limited spectrum necessitates the
development of dynamic spectrum access techniques, where users who have no spectrum licenses, also known as secondary
users, are allowed to use the temporarily unused licensed spectrum. For this purpose we have to know the presence or
absence of primary users for spectrum usage. So spectrums sensing is one of the major requirements of cognitive radio.Many
spectrum sensing techniques have been developed to sense the presence or absence of a licensed user. This paper evaluates
the performance of the energy detection based spectrum sensing technique in noisy and fading environments.The
performance of the energy detection technique will be evaluated by use of Receiver Operating Characteristics (ROC) curves
over additive white Gaussian noise (AWGN) and fading channels.
Comparative Study of Pre-Engineered and Conventional Steel Frames for Differe...irjes
In this paper, the conventional steel frames having triangular Pratt truss as a roofing system of 60 m
length, span 30m and varying bay spacing 4m, 5m and 6m respectively having eaves level for all the portals is at
10m and the EOT crane is supported at the height of 8m from ground level and pre-engineered steel frames of
same dimensions are analyzed and designed for wind zones (wind zone 2, wind zone 3, wind zone 4 and wind
zone 5) by using STAAD Pro V8i. The study deals with the comparative study of both conventional and preengineered
with respect to the amount of structural steel required, reduction in dead load of the structure.
Flip bifurcation and chaos control in discrete-time Prey-predator model irjes
The dynamics of discrete-time prey-predator model are investigated. The result indicates that the
model undergo a flip bifurcation which found by using center manifold theorem and bifurcation theory.
Numerical simulation not only illustrate our results, but also exhibit the complex dynamic behavior, such as the
periodic doubling in period-2, -4 -8, quasi- periodic orbits and chaotic set. Finally, the feedback control method
is used to stabilize chaotic orbits at an unstable interior point.
Energy Awareness and the Role of “Critical Mass” In Smart Citiesirjes
A Smart City could be depicted as a place, logical and physical, in which a crowd of heterogeneous
entities is related in time and space through different types of interactions. Any type of entity, whether it is a
device or a person, clustered in communities, becomes a source of context-based data.
Energy awareness is able to drive the process of bringing our society to limit energy waste and to optimize
usage of available resources, causing a strong environmental and social impact. Then, following social network
analysis methodologies related to the dynamics of complex systems, it is possible to find out, emergent and
sometimes hidden new habits of electricity usage. Through an initial Critical Mass, involving a multitude of
consumers, each related to more contexts, we evaluate the triggering and spreading of a collective attitude. To
this aim, in this paper, we propose a novel analytical model defining a new concept of critical mass, which
includes centrality measures both in a single layer and in a multilayer social network.
A Firefly Algorithm for Optimizing Spur Gear Parameters Under Non-Lubricated ...irjes
Firefly algorithm is one of the emerging evolutionary approaches for complex and non-linear
optimization problems. It is inspired by natural firefly‟s behavior such as movement of fireflies based on
brightness and by overcoming the constraints such as light absorption, obstacles, distance, etc. In this research,
firefly‟s movement had been simulated computationally to identify the best parameters for spur gear pair by
considering the design and manufacturing constraints. The proposed algorithm was tested with the traditional
design parameters and found the results are at par in less computational time by satisfying the constraints.
The Effect of Orientation of Vortex Generators on Aerodynamic Drag Reduction ...irjes
One of the main reasons for the aerodynamic drag in automotive vehicles is the flow separation
near the vehicle’s rear end. To delay this flow separation, vortex generators are used in recent vehicles. The
vortex generators are commonly used in aircrafts to prevent flow separation. Even though vortex generators
themselves create drag, but they also reduce drag by delaying flow separation at downstream. The overall effect
of vortex generators is more beneficial and proved by experimentation. The effect depends on the shape,size and
orientation of vortex generators. Hence optimized shape with proper orientation is essential for getting better
results.This paper presents the effect of vortex generators at different orientation to the flow field and the
mechanism by which these effects takes place.
An Assessment of The Relationship Between The Availability of Financial Resou...irjes
The availability of financial resources is an important element in impacting the success of a planning
process for an effective physical planning. The extent to which however, they are articulated in the process
remained elusive both in scholarly and public discourse. The objective of this study wastherefore, to examine
the extent to which financial resources affect physical planning. In doing so, the study examinedwhether
financial resources were adequate or not to facilitate planning processes in Paidha. According to the study
findings,budget prioritization and ceilings are still a challenge in Paidha Town Council. This is partly due
limited level of knowledge of physical planning among the officials of Paidha Town Council. As a result, there
were no dedicated budget line for routine inspection of physical development plan compliance and enforcement
tools in Paidha. In conclusion, in addressing uncoordinated patterns of physical development that characterize
Uganda‟s urban centres, a critical starting point ought to be the analysis of physical planning process. The
research of this kind is not only significant to other emerging urban centres facing poor a road network,
mushrooming informal settlements and poor social services including poor pattern of residential and commercial
developments but also to all institutions that are involved in planning these towns. Knowing the extent of need
for financial influences in planning may assist local authorities to take the processes of planning seriously which
will help enhance the sustainable development of emerging urban centres including Paidha.
The Choice of Antenatal Care and Delivery Place in Surabaya (Based on Prefere...irjes
- Person's desire to do a pregnancy examination is determined by the service place that suits the tastes
and facilities owned by it. Until now, the utilization of antenatal care by pregnant women is still low (Mardiana,
2014). The purpose of the study is to analyze factors affecting the utilization of antenatal care and delivery place
in Surabaya city based on the preferences and choice theory.
Type of survey research is cross sectional approach, the population is mothers who have children aged 1-
12 months in Surabaya. The large sample of 250 mothers who have children aged 1-12 months in 2013 is taken
by simple random sampling technique. Variables of the research are the preference elements and steps, choice
elements and steps, utilization of antenatal care and delivery place. Data were collected through questionnaires
and secondary data were then analyzed with descriptive statistics in the form of a frequency distribution, shown
by the schematic diagram.
The result showed that the preference elements and steps showed almost half (42.9%) desire to give birth
in a health care because of information got from someone else, while the choice element and step shows the
bulk (57.1%) of the criteria of delivery place chosen is a safe, comfortable and cheap delivery place, the labor
place which is the main choice most (57.1%) is cheap, comfortable, close.
Conclusion of the research based on the preferences and choice theory can be found three (3) new
theories, they are preferences become choice, preferences do not become choice, choice is preceded by
preferences
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
International Refereed Journal of Engineering and Science (IRJES)
1. International Refereed Journal of Engineering and Science (IRJES)
ISSN (Online) 2319-183X, (Print) 2319-1821
Volume 2, Issue 5(May 2013), PP.40-45
www.irjes.com
www.irjes.com 40 | Page
Heuristic Based Resource Allocation Using Virtual Machine
Migration: A Cloud Computing Perspective
Ts`epoMofolo1
, R Suchithra2
1,2
MS (IT) Department, Jain University Bangalore, India
Abstract: The emerging cloud computing paradigm provides administrators and IT organizations with
tremendous freedom to dynamically migrate virtualized computing services between physical servers in cloud
data centers. Virtualization and VM migration capabilities enable the data center to consolidate their
computing services and use minimal number of physical servers. VM migration offers great benefits such as
load balancing, server consolidation, online maintenance and proactive fault tolerance. However, in cloud
computing environments the cost of VM migration requires thorough consideration. Each VM migration may
result in SLA violation, hence it is essential to minimize the number of migrations to the extent possible. Failure
to do so will result in performance degradation and the cloud provider will have to incur the cost in monetary
terms. In previous works, the issue of SLA violation has not received thorough analysis. In this work, we devise
an algorithm that will keep the migration time minimum as well as minimizing the number of migrations. This
will play a major role in avoiding the performance degradation encountered by a migrating VM.
I. INTRODUCTION
Cloud Computing is proving to be a phenomenal technology where computing services are provided
over the computer networks, with on-demand elastic resources like computing energy, storage capacity, memory
and network [1]. Virtualization provides an efficient solution to the objectives of the cloud computing paradigm
by facilitating creation of Virtual Machines (VMs) over the underlying physical servers, leading to improved
resource utilization and abstraction. Virtualization refers to creating a virtual version of a device or a resource
such as a server, a storage device, network or even operating system where the mechanism divides the resource
into one or more execution environments. Devices, applications and end-users interact with the virtual resource
as if it were a real single logical resource. The factors that a cloud provider must take into account are elasticity,
scalability, live migration of VMs and performance isolation. Live migration of VMs, the process of
dynamically transferring a virtual machine across different servers on the fly, has proved to represent a new
opportunity to enable agile and dynamic resource management in modern data centers [2]. This is of utmost
importance since data center networks are fraught with scalability and efficiency issues, which have become
aspects of concern among practitioners and researchers [2]. The resource allocation algorithms take the resource
requirements of a VM into account and changes the allocated resources, thus making it an on demand elastic
cloud. VM placement and migration have become an integral part of resource allocation in cloud data centers.
Changes in the resource requirements of VMs are significant information for VM placement and migration
considerations. In our previous work in [3], we have emphasized that techniques that ensure very little
utilization of resources as a result of the VM migration should not be developed as it leads to high downtime
and subsequently service degradation which is not desirable in cloud platforms. Dynamic consolidation methods
which aim at minimizing the number of migrations as much as possible should be employed in cloud
computing. In a cloud, placement algorithms have a major responsibility of efficiently placing VMs on a
physical hosts. In this work, we present a VM placement algorithm which takes into account the resource
utilizations of a physical servers by the executing the VMs. The consumed resources are classified as CPU,
RAM and the network bandwidth. The storage capacity resource is not taken into consideration in this work
since we assume Network Attached Storage environments.Based on the data gathered from the resource
utilization we apply the VM placement algorithm.Our work is based on the cloud infrastructure depicted below:
2. Heuristic Based Resource Allocation Using Virtual Machine Migration: A…
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Figure 1: Layered Cloud Computing Architecture [11]
II. RELATED WORK
Some work on carrying out VM migrations while meeting SLA violations has been conducted in recent
researches. Jung et al. [5, 6] have studied the problem of dynamic consolidation of VMs executing multi-tier
web-application using live migration while meeting SLA requirements. They model SLA requirements as the
response time pre-calculated for each type of transactions specific to the web-application. They result in a new
VM placement using bin packing algorithm and gradient search techniques. The migration manager determines
whether there is a reconfiguration that is effective based on the utility function that accounts for the SLA
fulfillment. However, this mechanism can only be applicable to a single web-application environment and,
therefore it cannot be incorporated into a multi-tenant Infrastructure as a Service (IaaS) environment. In [7], Zhu
et al. have investigated a similar scenario of automated resource allocation and capacity planning. They
proposed three individual controllers each executing at a different time scale as follows: longest time scale
(hours to days), shorter time scale (minutes) and shortest time scale (seconds). These three controllers place
compatible workloads onto groups of servers, react to changing conditions by reallocating VMs, and allocate
resources to VMs within the servers to fulfill the imposed SLAs. The middle-scale controller applies a technique
based on the idea of setting fixed utilization thresholds. However, fixed thresholds are not suitable for IaaS
environments with dynamic workloads that exhibit non-stationary resource utilization patterns [4].In [8], Kumar
et al. have proposed a technique for dynamic VM consolidation based on an estimation of “Stability”- the
probability that a proposed VM reallocation will remain effective for a certain period of time in the future.
Predictions of future resource demands of applications are carried out using a time-variant probability density
function. The main drawback is that the authors have assumed that the metrics of distribution such as standard
deviation and mean are known a priori. They further assumed that these values can be obtained using offline
profiling of applications and online calibration. However, offline profiling is unrealistic for IaaS environments.
Furthermore, the authors have assumed that the resource utilization follows a normal distribution. However, it
has been proved that resource consumption by applications as well as VMs is more complex and cannot be
modelled using simple probability distribution.
In [9], Berral et al have investigated the problem the problem of dynamic consolidation of VMs
executing applications with deadlines that are defined in the SLAs. Using machine learning techniques, they
optimize the combination of power consumption and SLA fulfillment. The proposed mechanism is designed for
certain environments, such as High Performance Computing (HPC), where applications have deadline
constraints. Hence, such a mechanism is not suitable and feasible for infrastructures with variable workloads.
According to Blagodurov et al. in [10], servers in most data centers are often underutilized due to concerns
about SLA violations that may result from resource contention as physical server utilization increases. To
mitigate this issue they assume a virtualized data center that uses work conserving approach (that is, physical
resources are shared among hosted VMs). The work conserving approach however, typically leads to higher
utilization but no resource access guarantees can be made. This situation is highly undesirable in cloud data
centers. Their solution is to consolidate both batch and interactive workloads on each server, enabling a very
high utilization level (80% and above). At higher utilizations, the performance of the hosted workloads is likely
to degrade due to shared server resources. This is prevented by providing prioritized access to the physical
resources using Linux Control Groups (cgroups) CPU shares. The authors ensure that critical workloads have
preferred access to physical resources such that they exhibit similar performance when consolidated with non-
critical workloads as compared to when they are not. This is not applicable in IaaS infrastructure as applications
exhibit varying workloads over time.In this work, we pay more attention on the increasing CPU utilization that
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increases due to VMs executions on the physical server over time as well as contention of resources from other
applications which maybe executing on the physical server under consideration. Other physical server resource
constraints such as the memory and the network bandwidth are taken into consideration while carrying out the
VM migration process. We demonstrate techniques for achieving minimal number of migrations as well as
minimal migration durations in cloud data center. We carry out the experiments using the CloudSim simulation
toolkit [11].
III. HEURISTIC BASED VM PLACEMENT
The heuristic based VM migration scenario is partitioned as follows:
1. Determining when a physical server is considered to be overloaded requiring live migration of one or
more VMs from the physical server under consideration.
2. Determining when a physical server is considered as being under loaded hence it becomes a good
candidate for hosting VMs that are being migrated from overloaded physical servers.
3. Selection of VMs that should be migrated from an overloaded physical server. VM selection policy
(algorithm) has to be applied to carry out the selection process.
4. Finding a new placement of the VMs selected for migration from the overload and physical servers and
finding the best physical
The VM placement problem can be considered as a bin packing problem with variable been sizes and
items, where bins represent the physical servers, items represent the VMs to be allocated, and bin sizes represent
the available CPU capacities of those nodes. Since bin packing problem is NP-hard, to incorporate it into our
solution we apply a modification of the Best Fit Decreasing (BFD) algorithm that uses no more than
11
9
𝑍 𝐼 +
4 bins (where Z is the number of bins that provides the optimal solution). In simpler terms it has been proven
that 𝐵𝐹𝐷 𝐼 ≤
11
9
𝑍 𝐼 + 4 for all instances of I. In the modified BFD algorithm, we take as an input the
sorted list of VMs to be migrated in descending order of their current CPU utilizations and allocate each to a
selected host that provides the least number of remaining processing capacity caused by the allocation. The host
list is also sorted in decreasing order of their remaining capacity to ensure that a VM is allocated to a host that
has enough resources for it with the least number of attempts. This ensure high resource utilization as the
resources on the target host will not be idle.
The algorithm is presented below. It has the time complexity of nm, where n is the number of physical
target hosts and m is the number of VMs that have been selected for migration.
Modified Best Fit Decreasing Algorithm:
1. Input: SortedlistofTargetHosts, SortedVmList, Output: VMs allocations
2. Foreach VM in SortedVmList do
3. minCapacity←MAX
4. allocatedHost←NULL
5. Foreach host in sortedListofTargetHosts do
6. If target host has enough resources for VM
7. Capacity←estimateCapacity(host,vm)
8. If Capacity<minCapacity
9. Allocated host←host
10. minCapacity←Capacity
11. If allocatedHost≠NULL then
12. Allocation.add(vm,allocatedHost)
13. Return allocation
IV. EMPIRICAL STUDY AND EXPERIMENTAL SETUP
Our empirical study seeks to achieve the following goals:
(i) Carrying out the live migration of VMs in a manner that preserves free resources in order to prevent
SLA violations
(ii) Optimal utilization of resources
(iii) Performing minimal number of migrations to the extent possible
(iv) Efficient server consolidation through VM migrations
To this end we came up with a modified best fit decreasing algorithm which performs the migration
based on the above mentioned objectives. This algorithm is plays the role of a VM Placement policy and is
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implemented through the Cloudsim simulation toolkit which is open source and it plays an important role in
guaranteeing statistical significance.
We adopt the following test bed in our simulations:
Processor: Intel (R) Core(TM) i5- 2430M CPU @ 2.40 GHz
OS: Windows 8
RAM: 6GB
System Type: 64-bit OS, x64-based Processor
Storage Capacity: 500 GB
Softwares: JDK 1.7 and Netbeans 7.2
CloudSim 3.01 Configurations.
Scheduling Interval: 300
Simulation Limit : 24*60*60
Job Length= Random
Dynamic Workload
VM Types: 4
VM Ram: {880, 1730, 1740, 620}
VM Bandwidth: 100000 (100Mbits)
VM Storage Capacity: 2000 (2GB)
Host Types : HP Proliant ML110 G4 (1x [Xeon 3040 1860 MHz, 2 Cores], 4GB)
HP Proliant ML110 G5 (1x [Xeon 3075 2660 MHz, 2 Cores], 4GB)
Host MIPS= {1870, 2770}
RAM= {4096, 4096}
Bandwidth= 1 000 000 (1 Gbit/s)
Storage Capacity= 1 000 000 (1 GB)
DATA CENTER
System Architecture= x86
OS= linux
VMM= Xen
Number of physical hosts=50
Number of VMs = 60
To validate and understand the efficiency of our algorithm we carry out experiments that are based on
dynamic workload loads generated as is the case in real world cloud data centers. Our modified best fit
decreasing algorithm makes use of the already available policies in Cloudsim simulation toolkit to achieve the
desired objectives. The already existing policies include the minimum migration policy which has been proved
to be more efficient than the other evaluated policies.
V. ANALYSIS OF RESULTS
The first experiment is based on local regression robust VM allocation policy and the second is based
on the modified best fit decreasing algorithm that we devised. Statistical analysis of the simulations of both
algorithms is presented below.
Simulations Analysis
Column1 Column3 Column2
Simulation 1 Simulation 2
Number of VM migrations 3537 4172
SLA 0.06023 0.06431
SLA perf degradation due to
migration 0.26 0.32
SLA time per active host 22.92 20.13
Overall SLA violation 8.11 7.42
Average SLA violation 17.31 16.14
Number of host shutdowns 927 1346
Table 1: General Simulation Results
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Column1 Column3 Column2
Simulation 1 Simulation 2
Mean time before a host shutdown 910.38 692.28
StDev time before a host shutdown 1556.8 815.96
Mean time before a VM migration 15.76 17.03
StDev time before a VM migration 7.38 7.8
Execution time - VM selection mean 0.00009 0.00014
Execution time - VM selection stDev 0.00029 0.00035
Execution time - host selection mean 0.00036 0.00038
Execution time - host selection stDev 0.00059 0.00049
Execution time - VM reallocation
mean 0.00195 0.00105
Execution time - VM reallocation
stDev 0.00662 0.00182
Execution time - total mean 0.00751 0.00661
Execution time - total stDev 0.01296 0.01154
Table 2: Performance analysis based on time dimension
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VI. CONCLUDING REMARKS
Through our modified best fit decreasing algorithm we have achieved migrations of VMs on the basis
of overloading that occurs in physical servers in cloud data centers. As indicated in our results, our algorithm
provides relatively less performance degradation that occurs due to VM migrations. The SLA violation is also
less compared to other techniques and this means the cloud provider will incur less cost from VM migrations.
Further, our algorithm performs host selection and VM reallocation quicker than the existing algorithms.
Maintenance of physical servers can be efficiently achieved through our algorithm as it leads to efficient
consolidation of VMs.
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