This document summarizes several techniques for live virtual machine migration in cloud computing. It discusses works that have proposed affinity-aware migration models to improve resource utilization, energy efficient migration approaches using storage migration and live VM migration, and a dynamic consolidation technique using migration control to avoid unnecessary migrations. The document also summarizes works that have designed methods to minimize migration downtime and network traffic, proposed a resource reservation framework for efficient migration of multiple VMs, and addressed real-time issues in live migration. Finally, it provides a table summarizing the techniques, tools used, and potential future work or gaps identified for each discussed work.
An Efficient Cloud Scheduling Algorithm for the Conservation of Energy throug...IJECEIAES
Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.
Emerging cloud computing paradigm vision, research challenges and development...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
MCCVA: A NEW APPROACH USING SVM AND KMEANS FOR LOAD BALANCING ON CLOUDijccsa
Nowadays, the demand of using resources, using services via the intranet system or on the Internet is rapidly growing. The respective problem coming is how to use these resources effectively in terms of time and quality. Therefore, the network QoS and its economy are people concerns, cloud computing was born in an inevitable trend. However, managing resources and scheduling tasks in virtualized data centres on the cloud are challenging tasks. Currently, there are a lot of Load Balancing algorithms applied in clouds and proposed by many authors, scholars, and experts. These existing methods are more about natural and heuristic, but the application of AI, or modern datamining technologies, in load balancing is not too popular due to the different characteristics of cloud. In this paper, we propose an algorithm to reduce the processing time (makespan) on cloud computing, helping the load balancing work more efficiency. Here, we use the SVM algorithm to classify the coming Requests, K - Mean to cluster the VMs in cloud, then the LB will allocate the requests into the VMs in the most reasonable way. In this way, request with the least processing time will be allocated to the VMs with the lowest usage. We name this new proposal as MCCVA - Makespan Classification & Clustering VM Algorithm. We have experimented and evaluated this algorithm in CloudSim, a cloud simulation environment, we obtained better results than some other wellknown algorithms. With this MCCVA, we can see the big potential of AI and datamining in Load Balancing, we can further develop LB with AI to achieve better and better results of QoS.
Energy efficient utilization of data center resources can be carried out by optimization of the resources allocated in virtual machine placement through live migration. This paper proposes a method to optimize virtual machine placement in Banker algorithm for energy efficient cloud computing to tackle the issue of load balancing for hotspot mitigation and proposed method is named as Optimized Virtual Machine Placement in Banker algorithm (OVMPBA). By determining the state of host overload through dynamic thresholds technique and minimization migration policy for VM selection from the overloaded host an attempt is made to efficiently utilize the available computing resources and thus minimize the energy consumption in the cloud environment. The above research work is experimentally simulated on CloudSim Simulator and the experimental result shows that proposed OVMPBA method provides better energy efficiency and lesser number of migrations against existing methods of host overload detection-virtual machine selection and therefore maximizes the cloud energy efficiency.
Scheduling in Virtual Infrastructure for High-Throughput Computing IJCSEA Journal
For the execution of the scientific applications, different methods have been proposed to dynamically provide execution environments for such applications that hide the complexity of underlying distributed and heterogeneous infrastructures. Recently virtualization has emerged as a promising technology to provide such environments. Virtualization is a technology that abstracts away the details of physical hardware and provides virtualized resources for high-level scientific applications. Virtualization offers a cost-effective and flexible way to use and manage computing resources. Such an abstraction is appealing in Grid computing and Cloud computing for better matching jobs (applications) to computational resources. This work applies the virtualization concept to the Condor dynamic resource management system by using Condor Virtual Universe to harvest the existing virtual computing resources to their maximum utility. It allows existing computing resources to be dynamically provisioned at run-time by users based on application requirements instead of statically at design-time thereby lay the basis for efficient use of the
available resources, thus providing way for the efficient use of the available resources.
Agent based Aggregation of Cloud Services- A Research Agendaidescitation
-Cloud computing has come to the forefront as it
overcomes some of the issues in computing such as storage
space and processing power. It enables ubiquitous accessing
and processing of information without the need of excessive
computing facilities. In this work, we plan to brief some of the
issues in aggregating the cloud services, discovering futuristic
cloud service requests, develop a repository of the same and
propose an agent based Quality of Service (QoS) provisioning
system for cloud clients.
An Efficient Cloud Scheduling Algorithm for the Conservation of Energy throug...IJECEIAES
Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.
Emerging cloud computing paradigm vision, research challenges and development...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
MCCVA: A NEW APPROACH USING SVM AND KMEANS FOR LOAD BALANCING ON CLOUDijccsa
Nowadays, the demand of using resources, using services via the intranet system or on the Internet is rapidly growing. The respective problem coming is how to use these resources effectively in terms of time and quality. Therefore, the network QoS and its economy are people concerns, cloud computing was born in an inevitable trend. However, managing resources and scheduling tasks in virtualized data centres on the cloud are challenging tasks. Currently, there are a lot of Load Balancing algorithms applied in clouds and proposed by many authors, scholars, and experts. These existing methods are more about natural and heuristic, but the application of AI, or modern datamining technologies, in load balancing is not too popular due to the different characteristics of cloud. In this paper, we propose an algorithm to reduce the processing time (makespan) on cloud computing, helping the load balancing work more efficiency. Here, we use the SVM algorithm to classify the coming Requests, K - Mean to cluster the VMs in cloud, then the LB will allocate the requests into the VMs in the most reasonable way. In this way, request with the least processing time will be allocated to the VMs with the lowest usage. We name this new proposal as MCCVA - Makespan Classification & Clustering VM Algorithm. We have experimented and evaluated this algorithm in CloudSim, a cloud simulation environment, we obtained better results than some other wellknown algorithms. With this MCCVA, we can see the big potential of AI and datamining in Load Balancing, we can further develop LB with AI to achieve better and better results of QoS.
Energy efficient utilization of data center resources can be carried out by optimization of the resources allocated in virtual machine placement through live migration. This paper proposes a method to optimize virtual machine placement in Banker algorithm for energy efficient cloud computing to tackle the issue of load balancing for hotspot mitigation and proposed method is named as Optimized Virtual Machine Placement in Banker algorithm (OVMPBA). By determining the state of host overload through dynamic thresholds technique and minimization migration policy for VM selection from the overloaded host an attempt is made to efficiently utilize the available computing resources and thus minimize the energy consumption in the cloud environment. The above research work is experimentally simulated on CloudSim Simulator and the experimental result shows that proposed OVMPBA method provides better energy efficiency and lesser number of migrations against existing methods of host overload detection-virtual machine selection and therefore maximizes the cloud energy efficiency.
Scheduling in Virtual Infrastructure for High-Throughput Computing IJCSEA Journal
For the execution of the scientific applications, different methods have been proposed to dynamically provide execution environments for such applications that hide the complexity of underlying distributed and heterogeneous infrastructures. Recently virtualization has emerged as a promising technology to provide such environments. Virtualization is a technology that abstracts away the details of physical hardware and provides virtualized resources for high-level scientific applications. Virtualization offers a cost-effective and flexible way to use and manage computing resources. Such an abstraction is appealing in Grid computing and Cloud computing for better matching jobs (applications) to computational resources. This work applies the virtualization concept to the Condor dynamic resource management system by using Condor Virtual Universe to harvest the existing virtual computing resources to their maximum utility. It allows existing computing resources to be dynamically provisioned at run-time by users based on application requirements instead of statically at design-time thereby lay the basis for efficient use of the
available resources, thus providing way for the efficient use of the available resources.
Agent based Aggregation of Cloud Services- A Research Agendaidescitation
-Cloud computing has come to the forefront as it
overcomes some of the issues in computing such as storage
space and processing power. It enables ubiquitous accessing
and processing of information without the need of excessive
computing facilities. In this work, we plan to brief some of the
issues in aggregating the cloud services, discovering futuristic
cloud service requests, develop a repository of the same and
propose an agent based Quality of Service (QoS) provisioning
system for cloud clients.
A review on serverless architectures - function as a service (FaaS) in cloud ...TELKOMNIKA JOURNAL
Emergence of cloud computing as the inevitable IT computing paradigm, the perception of the compute reference model and building of services has evolved into new dimensions. Serverless computing is an execution model in which the cloud service provider dynamically manages the allocation of compute resources of the server. The consumer is billed for the actual volume of resources consumed by them, instead paying for the pre-purchased units of compute capacity. This model evolved as a way to achieve optimum cost, minimum configuration overheads, and increases the application's ability to scale in the cloud. The prospective of the serverless compute model is well conceived by the major cloud service providers and reflected in the adoption of serverless computing paradigm. This review paper presents a comprehensive study on serverless computing architecture and also extends an experimentation of the working principle of serverless computing reference model adapted by AWS Lambda. The various research avenues in serverless computing are identified and presented.
Efficient architectural framework of cloud computing Souvik Pal
Cloud computing is that enables adaptive, favorable and on-demand network access to a collective pool of adjustable and configurable computing physical resources which networks, servers, bandwidth, storage that can be swiftly provisioned and released with negligible supervision endeavor or service provider interaction. From business prospective, the viable achievements of Cloud Computing and recent developments in Grid computing have brought the platform that has introduced virtualization technology into the era of high performance computing. However, clouds are Internet-based concept and try to disguise complexity overhead for end users. Cloud service providers (CSPs) use many structural designs combined with self-service capabilities and ready-to-use facilities for computing resources, which are enabled through network infrastructure especially the internet which is an important consideration. This paper provides an efficient architectural Framework for cloud computing that may lead to better performance and faster access.
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.
A cloud broker approach with qos attendance and soa for hybrid cloud computin...csandit
Cloud Computing is the industry whose demand has been growing continuously since its
appearance as a solution that offers different types of computing resources as a service over the
Internet. The number of cloud computing providers grows into a run, while the end user is
currently in the position of having many pricing options, distinct features and performance for
the same required service. This work is inserted in the cloud computing task scheduling
research field to hybrid cloud environments with service-oriented architecture (SOA), dynamic
allocation and control of services and QoS requirements attendance. Therefore, it is proposed
the QBroker Architecture, representing a cloud broker with trading features that implement the
intermediation services, defined by the NIST Cloud Computing Reference Model. An
experimental design was created in order to demonstrate compliance to the QoS requirement of
maximum task execution time, the differentiation of services and dynamic allocation of services.
The experimental results obtained by simulation with CloudSim prove that QBroker has the
necessary requirements to provide QoS improvement in hybrid cloud computing environments
based on SOA.
ENERGY-EFFICIENT ADAPTIVE RESOURCE MANAGEMENT FOR REAL-TIME VEHICULAR CLOUD S...Nexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
Abstract: Efficient task scheduling method can meet users' requirements, and improve the resource utilization, then increase the overall performance of the cloud computing environment. Cloud computing has new features, such as flexibility, Virtualization and etc., in this paper we propose a two levels task scheduling method based on load balancing in cloud computing. This task scheduling method meet user's requirements and get high resource utilization that simulation results in Cloud Sim simulator prove this.Keywords: cloud computing; task scheduling; virtualization.
Title: A Task Scheduling Algorithm in Cloud Computing
Author: Ali Bagherinia
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
Opportunistic job sharing for mobile cloud computingijccsa
Cloud Computing is the evolution of new business era which is covered with many of technologies.These
technology are taking advantage of economies of scale and multi tenancy which are used to decrees the
cost of information technology resources. Many of the organization are eager to reduce their computing
cost through the means of virtualization. This demand of reducing the computing cost and time has led to
the innovation of Cloud Computing. Itenhanced computing through improved deployment and
infrastructure costs and processing time. Mobile computing & its applications in smart phones enable a
new, rich user experience. Due to extreme usage of limited resources in smart phones it create problems
which are battery problems, memory space and CPU. To solve this problem, we propose a dynamic mobile
cloud computing architecture framework to use global resources instead of local resources. In this
proposed framework the usefulness of job sharing workload at runtime reduces the load at the local client
and the dynamic throughput time of the job through Wi-Fi Connectivity.
Profit Maximization for Service Providers using Hybrid Pricing in Cloud Compu...Editor IJCATR
Cloud computing has recently emerged as one of the buzzwords in the IT industry. Several IT vendors are promising to offer computation, data/storage, and application hosting services, offering Service-Level Agreements (SLA) backed performance and uptime promises for their services. While these „clouds‟ are the natural evolution of traditional clusters and data centers, they are distinguished by following a pricing model where customers are charged based on their utilization of computational resources, storage and transfer of data. They offer subscription-based access to infrastructure, platforms, and applications that are popularly termed as IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). In order to improve the profit of service providers we implement a technique called hybrid pricing , where this hybrid pricing model is a pooled with fixed and spot pricing techniques.
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.
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.
Power consumption prediction in cloud data center using machine learningIJECEIAES
The flourishing development of the cloud computing paradigm provides several ser- vices in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.
Swiftly increasing demand of computational
calculations in the process of business, transferring of files
under certain protocols and data centers force to develop an
emerging technology cater to the services for computational
need, highly manageable and secure storage. To fulfill these
technological desires cloud computing is the best answer by
introducing various sorts of service platforms in high
computational environment. Cloud computing is the most
recent paradigm promising to turn around the vision of
“computing utilities” into reality. The term “cloud
computing” is relatively new, there is no universal agreement
on this definition. In this paper, we go through with different
area of expertise of research and novelty in cloud computing
domain and its usefulness in the genre of management. Even
though the cloud computing provides many distinguished
features, it still has certain sorts of short comings amidst with
comparatively high cost for both private and public clouds. It
is the way of congregating amasses of information and
resources stored in personal computers and other gadgets
and further putting them on the public cloud for serving
users. Resource management in a cloud environment is a
hard problem, due to the scale of modern data centers, their
interdependencies along with the range of objectives of the
different actors in a cloud ecosystem. Cloud computing is
turning to be one of the most explosively expanding
technologies in the computing industry in this era. It
authorizes the users to transfer their data and computation to
remote location with minimal impact on system performance.
With the evolution of virtualization technology, cloud
computing has been emerged to be distributed systematically
or strategically on full basis. The idea of cloud computing has
not only restored the field of distributed systems but also
fundamentally changed how business utilizes computing
today. Resource management in cloud computing is in fact a
typical problem which is due to the scale of modern data
centers, the variety of resource types and their inter
dependencies, unpredictability of load along with the range of
objectives of the different actors in a cloud ecosystem.
A hybrid algorithm to reduce energy consumption management in cloud data centersIJECEIAES
There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses on load balancing methods as they act dynamically because of their dependence on the current behavior of system. By taking a detailed look on previous methods, we provide a hybrid method which enables us to save energy through finding a suitable configuration for virtual machines placement and considering special features of virtual environments for scheduling and balancing dynamic loads by live migration method.
DESIGNING ASPECT AND FUNCTIONALITY ISSUES OF CLOUD BROKERING SERVICE IN CLOUD...Souvik Pal
Cloud brokering service is an intermediate service which enables the producer-consumer business model
enforcing the easy access to cloud services from Cloud Service Providers (CSPs). Cloud broker is to
provide a platform where broker collects the information from the user, analyze the data, and sends those
data to the CSPs. Cloud broker also provides data integration services and modeling the data across all the
components or units of the cloud services. This paper deals with designing criteria and issues of cloud
broker, system activity of broker, and sequence diagram of system design with implementation procedure.
A Survey on Virtualization Data Centers For Green Cloud ComputingIJTET Journal
Abstract —Due to trends like Cloud Computing and Green cloud Computing, virtualization technologies are gaining increasing importance. Cloud is a atypical model for computing resources, which intent to computing framework to the network in order to cut down costs of software and hardware resources. Nowadays, power is one of big issue of IDC has huge impacts on society. Researchers are seeking to find solutions to make IDC reduce power consumption. These IDC (Internet Data Center) consume large amounts of energy to process the cloud services, high operational cost, and affecting the lifespan of hardware equipments. The field of Green computing is also becoming more and more important in a world with finite number of energy resources and rising demand. Virtual Machine (VM) mechanism has been broadly applied in data center, including flexibility, reliability, and manageability. The research survey presents about the virtualization IDC in green cloud it contains various key features of the Green cloud, cloud computing, data centers, virtualization, data center with virtualization, power – aware, thermal – aware, network-aware, resource-aware and migration techniques. In this paper the several methods that are utilze to achieve the virtualization in IDC in green cloud computing are discussed.
Virtual Machine Migration Techniques in Cloud Environment: A Surveyijsrd.com
Cloud is an emerging technology in the world of information technology and is built on the key concept of virtualization. Virtualization separates hardware from software and has benefits of server consolidation and live migration. Live migration is a useful tool for migrating OS instances across distant physical of data centers and clusters. It facilitates load balancing, fault management, low-level system maintenance and reduction in energy consumption. In this paper, we survey the major issues of virtual machine live migration. There are various techniques available for live migration and different parameters are considered for migration.
A review on serverless architectures - function as a service (FaaS) in cloud ...TELKOMNIKA JOURNAL
Emergence of cloud computing as the inevitable IT computing paradigm, the perception of the compute reference model and building of services has evolved into new dimensions. Serverless computing is an execution model in which the cloud service provider dynamically manages the allocation of compute resources of the server. The consumer is billed for the actual volume of resources consumed by them, instead paying for the pre-purchased units of compute capacity. This model evolved as a way to achieve optimum cost, minimum configuration overheads, and increases the application's ability to scale in the cloud. The prospective of the serverless compute model is well conceived by the major cloud service providers and reflected in the adoption of serverless computing paradigm. This review paper presents a comprehensive study on serverless computing architecture and also extends an experimentation of the working principle of serverless computing reference model adapted by AWS Lambda. The various research avenues in serverless computing are identified and presented.
Efficient architectural framework of cloud computing Souvik Pal
Cloud computing is that enables adaptive, favorable and on-demand network access to a collective pool of adjustable and configurable computing physical resources which networks, servers, bandwidth, storage that can be swiftly provisioned and released with negligible supervision endeavor or service provider interaction. From business prospective, the viable achievements of Cloud Computing and recent developments in Grid computing have brought the platform that has introduced virtualization technology into the era of high performance computing. However, clouds are Internet-based concept and try to disguise complexity overhead for end users. Cloud service providers (CSPs) use many structural designs combined with self-service capabilities and ready-to-use facilities for computing resources, which are enabled through network infrastructure especially the internet which is an important consideration. This paper provides an efficient architectural Framework for cloud computing that may lead to better performance and faster access.
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.
A cloud broker approach with qos attendance and soa for hybrid cloud computin...csandit
Cloud Computing is the industry whose demand has been growing continuously since its
appearance as a solution that offers different types of computing resources as a service over the
Internet. The number of cloud computing providers grows into a run, while the end user is
currently in the position of having many pricing options, distinct features and performance for
the same required service. This work is inserted in the cloud computing task scheduling
research field to hybrid cloud environments with service-oriented architecture (SOA), dynamic
allocation and control of services and QoS requirements attendance. Therefore, it is proposed
the QBroker Architecture, representing a cloud broker with trading features that implement the
intermediation services, defined by the NIST Cloud Computing Reference Model. An
experimental design was created in order to demonstrate compliance to the QoS requirement of
maximum task execution time, the differentiation of services and dynamic allocation of services.
The experimental results obtained by simulation with CloudSim prove that QBroker has the
necessary requirements to provide QoS improvement in hybrid cloud computing environments
based on SOA.
ENERGY-EFFICIENT ADAPTIVE RESOURCE MANAGEMENT FOR REAL-TIME VEHICULAR CLOUD S...Nexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
Abstract: Efficient task scheduling method can meet users' requirements, and improve the resource utilization, then increase the overall performance of the cloud computing environment. Cloud computing has new features, such as flexibility, Virtualization and etc., in this paper we propose a two levels task scheduling method based on load balancing in cloud computing. This task scheduling method meet user's requirements and get high resource utilization that simulation results in Cloud Sim simulator prove this.Keywords: cloud computing; task scheduling; virtualization.
Title: A Task Scheduling Algorithm in Cloud Computing
Author: Ali Bagherinia
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
Opportunistic job sharing for mobile cloud computingijccsa
Cloud Computing is the evolution of new business era which is covered with many of technologies.These
technology are taking advantage of economies of scale and multi tenancy which are used to decrees the
cost of information technology resources. Many of the organization are eager to reduce their computing
cost through the means of virtualization. This demand of reducing the computing cost and time has led to
the innovation of Cloud Computing. Itenhanced computing through improved deployment and
infrastructure costs and processing time. Mobile computing & its applications in smart phones enable a
new, rich user experience. Due to extreme usage of limited resources in smart phones it create problems
which are battery problems, memory space and CPU. To solve this problem, we propose a dynamic mobile
cloud computing architecture framework to use global resources instead of local resources. In this
proposed framework the usefulness of job sharing workload at runtime reduces the load at the local client
and the dynamic throughput time of the job through Wi-Fi Connectivity.
Profit Maximization for Service Providers using Hybrid Pricing in Cloud Compu...Editor IJCATR
Cloud computing has recently emerged as one of the buzzwords in the IT industry. Several IT vendors are promising to offer computation, data/storage, and application hosting services, offering Service-Level Agreements (SLA) backed performance and uptime promises for their services. While these „clouds‟ are the natural evolution of traditional clusters and data centers, they are distinguished by following a pricing model where customers are charged based on their utilization of computational resources, storage and transfer of data. They offer subscription-based access to infrastructure, platforms, and applications that are popularly termed as IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). In order to improve the profit of service providers we implement a technique called hybrid pricing , where this hybrid pricing model is a pooled with fixed and spot pricing techniques.
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.
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.
Power consumption prediction in cloud data center using machine learningIJECEIAES
The flourishing development of the cloud computing paradigm provides several ser- vices in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.
Swiftly increasing demand of computational
calculations in the process of business, transferring of files
under certain protocols and data centers force to develop an
emerging technology cater to the services for computational
need, highly manageable and secure storage. To fulfill these
technological desires cloud computing is the best answer by
introducing various sorts of service platforms in high
computational environment. Cloud computing is the most
recent paradigm promising to turn around the vision of
“computing utilities” into reality. The term “cloud
computing” is relatively new, there is no universal agreement
on this definition. In this paper, we go through with different
area of expertise of research and novelty in cloud computing
domain and its usefulness in the genre of management. Even
though the cloud computing provides many distinguished
features, it still has certain sorts of short comings amidst with
comparatively high cost for both private and public clouds. It
is the way of congregating amasses of information and
resources stored in personal computers and other gadgets
and further putting them on the public cloud for serving
users. Resource management in a cloud environment is a
hard problem, due to the scale of modern data centers, their
interdependencies along with the range of objectives of the
different actors in a cloud ecosystem. Cloud computing is
turning to be one of the most explosively expanding
technologies in the computing industry in this era. It
authorizes the users to transfer their data and computation to
remote location with minimal impact on system performance.
With the evolution of virtualization technology, cloud
computing has been emerged to be distributed systematically
or strategically on full basis. The idea of cloud computing has
not only restored the field of distributed systems but also
fundamentally changed how business utilizes computing
today. Resource management in cloud computing is in fact a
typical problem which is due to the scale of modern data
centers, the variety of resource types and their inter
dependencies, unpredictability of load along with the range of
objectives of the different actors in a cloud ecosystem.
A hybrid algorithm to reduce energy consumption management in cloud data centersIJECEIAES
There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses on load balancing methods as they act dynamically because of their dependence on the current behavior of system. By taking a detailed look on previous methods, we provide a hybrid method which enables us to save energy through finding a suitable configuration for virtual machines placement and considering special features of virtual environments for scheduling and balancing dynamic loads by live migration method.
DESIGNING ASPECT AND FUNCTIONALITY ISSUES OF CLOUD BROKERING SERVICE IN CLOUD...Souvik Pal
Cloud brokering service is an intermediate service which enables the producer-consumer business model
enforcing the easy access to cloud services from Cloud Service Providers (CSPs). Cloud broker is to
provide a platform where broker collects the information from the user, analyze the data, and sends those
data to the CSPs. Cloud broker also provides data integration services and modeling the data across all the
components or units of the cloud services. This paper deals with designing criteria and issues of cloud
broker, system activity of broker, and sequence diagram of system design with implementation procedure.
A Survey on Virtualization Data Centers For Green Cloud ComputingIJTET Journal
Abstract —Due to trends like Cloud Computing and Green cloud Computing, virtualization technologies are gaining increasing importance. Cloud is a atypical model for computing resources, which intent to computing framework to the network in order to cut down costs of software and hardware resources. Nowadays, power is one of big issue of IDC has huge impacts on society. Researchers are seeking to find solutions to make IDC reduce power consumption. These IDC (Internet Data Center) consume large amounts of energy to process the cloud services, high operational cost, and affecting the lifespan of hardware equipments. The field of Green computing is also becoming more and more important in a world with finite number of energy resources and rising demand. Virtual Machine (VM) mechanism has been broadly applied in data center, including flexibility, reliability, and manageability. The research survey presents about the virtualization IDC in green cloud it contains various key features of the Green cloud, cloud computing, data centers, virtualization, data center with virtualization, power – aware, thermal – aware, network-aware, resource-aware and migration techniques. In this paper the several methods that are utilze to achieve the virtualization in IDC in green cloud computing are discussed.
Virtual Machine Migration Techniques in Cloud Environment: A Surveyijsrd.com
Cloud is an emerging technology in the world of information technology and is built on the key concept of virtualization. Virtualization separates hardware from software and has benefits of server consolidation and live migration. Live migration is a useful tool for migrating OS instances across distant physical of data centers and clusters. It facilitates load balancing, fault management, low-level system maintenance and reduction in energy consumption. In this paper, we survey the major issues of virtual machine live migration. There are various techniques available for live migration and different parameters are considered for migration.
ENERGY EFFICIENT VIRTUAL MACHINE ASSIGNMENT BASED ON ENERGY CONSUMPTION AND R...IAEME Publication
Cloud Computing is an internet based computing which makes and different types of services available to users. For customers based on their required services over the internet virtualized resources are provided. The fast growth of cloud resources with customers demand increases the energy consumption results in carbon dioxide emission. However, energy consumption and carbon dioxide emission in cloud data centre have massive impact on global environment triggering intense research in this area. To minimize the energy consumption in this paper we propose VM Assignment scheduling algorithm, it is based energy consumption and balancing the resource utilization. we consider both the VM and host energy consumption and classify the VMs based the resource usage and schedule them to balance the resources utilization among the hosts in the cloud data centre which leads to better energy efficiency and reduces the heat generation. The effectiveness of the proposed technique has been verified by simulating on CloudSim. Experimental results confirm that the technique proposed here can significantly reduce energy consumption in cloud.
A survey on energy efficient with task consolidation in the virtualized cloud...eSAT Journals
Abstract Cloud computing is a new model of computing that is widely used in today’s industry, organizations and society in information technology service delivery as a utility. It enables organizations to reduce operational expenditure and capital expenditure. However, cloud computing with underutilized resources still consumes an unacceptable amount of energy than fully utilized resource. Many techniques for optimizing energy consumption in virtualized cloud have been proposed. This paper surveys different energy efficient models with task consolidation in the virtualized cloud computing environment. Keywords: Cloud computing, Virtualization, Task consolidation, Energy consumption, Virtual machine
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
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.
A Virtualization Model for Cloud ComputingSouvik Pal
Cloud Computing is now a very emerging field in the IT industry as well as research field. The advancement of Cloud Computing came up due to fast-growing usage of internet among the people. Cloud Computing is basically on-demand network access to a collection of physical resources which can be provisioned according to the need of cloud user under the supervision of Cloud Service provider interaction. From business prospective, the viable achievements of Cloud Computing and recent developments in Grid computing have brought the platform that has introduced virtualization technology into the era of high performance computing. Virtualization technology is widely applied to modern data center for cloud computing. Virtualization is used computer resources to imitate other computer resources or whole computers. This paper provides a Virtualization model for cloud computing that may lead to faster access and better performance. This model may help to combine self-service capabilities and ready-to-use facilities for computing resources.
A Strategic Evaluation of Energy-Consumption and Total Execution Time for Clo...Souvik Pal
Cloud computing is a very budding area in the
research field and as well as in the IT enterprises. Cloud
Computing is basically on-demand network access to a
collection of physical resources which can be provisioned
according to the need of cloud user under the supervision of
Cloud Service provider interaction. In this era of rapid usage
of Internet all over the world, Cloud computing has become
the center of Internet-oriented business place. For enterprises,
cloud computing is the worthy of consideration and they try to
build business systems with minimal costs, higher profits and
more choice; for large-scale industry, energy consumption
and total execution tome are the two important aspects of
cloud computing. In the current scenario, IT Enterprises are
trying to minimize the energy-consumption which, in turn,
maximizes the profit of the industry. And they are also trying
to reduce total execution time which, in turn, is concerned
with providing better Quality of Service (QoS). Therefore, in
this paper we have made an attempt to evaluate energyconsumption
and total execution time using CloudSim
simulator which helps to make evaluation performance of
energy consumption and total execution time of user
application.
A Strategic Evaluation of Energy-Consumption and Total Execution Time for Clo...idescitation
Cloud computing is a very budding area in the
research field and as well as in the IT enterprises. Cloud
Computing is basically on-demand network access to a
collection of physical resources which can be provisioned
according to the need of cloud user under the supervision of
Cloud Service provider interaction. In this era of rapid usage
of Internet all over the world, Cloud computing has become
the center of Internet-oriented business place. For enterprises,
cloud computing is the worthy of consideration and they try to
build business systems with minimal costs, higher profits and
more choice; for large-scale industry, energy consumption
and total execution tome are the two important aspects of
cloud computing. In the current scenario, IT Enterprises are
trying to minimize the energy-consumption which, in turn,
maximizes the profit of the industry. And they are also trying
to reduce total execution time which, in turn, is concerned
with providing better Quality of Service (QoS). Therefore, in
this paper we have made an attempt to evaluate energy-
consumption and total execution time using CloudSim
simulator which helps to make evaluation performance of
energy consumption and total execution time of user
application.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Task Performance Analysis in Virtual Cloud EnvironmentRSIS International
Cloud computing based applications are beneficial for
businesses of all sizes and industries as they don’t have to invest
a huge amount on initial setup. This way, businesses can opt for
Cloud services and can implement innovative ideas. But
evaluating the performance of provisioning (e.g. CPU scheduling
and resource allocation) policies in a real Cloud computing
environment for different application techniques is challenging
because clouds show dynamic demands, workloads, supply
patterns, VM sizes, and resources (hardware, software, and
network). User’s requests and services requirements are
heterogeneous and dynamic. Applications models have
unpredictable performance, workloads, and dynamic scaling
requirements. So a demand for a Simulation toolkit for Cloud is
there. Cloudsim is self-contained simulation framework that
provides simulation and modeling of Cloud-based application in
lesser time with lesser efforts. In this paper we tried to simulate
the task performance of a cloudlet using one data center, one
VM. We also developed a Graphical User Interface to
dynamically change the simulation parameters and show
simulation results.
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.
Advancement in computing facilities marks back from 1960’s with introduction of mainframes. Each of the computing has one or the other issues, so keeping this in mind cloud computing was introduced. Cloud computing has its roots in older technologies such as hardware virtualization, distributed computing, internet technologies, and autonomic computing. Cloud computing can be described with two models, one is service model and second is deployment model. While providing several services, cloud management’s primary role is resource provisioning. While there are several such benefits of cloud computing, there are challenges in adopting public clouds because of dependency on infrastructure that is shared by many enterprises. In this paper, we present core knowledge of cloud computing, highlighting its key concepts, deployment models, service models, benefits as well as security issues related to cloud data. The aim of this paper is to provide a better understanding of the cloud computing and to identify important research directions in this field
Hybrid Based Resource Provisioning in CloudEditor IJCATR
The data centres and energy consumption characteristics of the various machines are often noted with different capacities.
The public cloud workloads of different priorities and performance requirements of various applications when analysed we had noted
some invariant reports about cloud. The Cloud data centres become capable of sensing an opportunity to present a different program.
In out proposed work, we are using a hybrid method for resource provisioning in data centres. This method is used to allocate the
resources at the working conditions and also for the energy stored in the power consumptions. Proposed method is used to allocate the
process behind the cloud storage.
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
A study to evaluate the attitude of faculty members of public universities of...
A survey on live virtual machine migrations and its techniques
1. Computer Engineering and Intelligent Systems www.iiste.org
ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online)
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110
A Survey on Live Virtual Machine Migrations and its Techniques
Swapnil M. Parikh
Department of Computer Science and Engineering, Babaria Institute of Technology,
BITS edu Campus, Varnama, Vadodara, Gujarat, India – 391240
swapnil.parikh@gmail.com
Abstract
Today’s world is internet world. Almost all the people uses internet for accessing different services. In Cloud
Computing various cloud consumers demand variety of services as per their dynamically changing needs over
the internet. So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But
due to the availability of finite resources it is very difficult for cloud providers to provide all the demanded
services in time. From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So,
it’s a vital issue to meet cloud consumers’ QoS requirements and satisfaction. Virtualization mainly abstracts the
resources like CPU and Memory through Virtual Machine for efficient resource utilization. Virtual Machine
Migration is one of the key technique for dynamic resource management in cloud computing. This paper mainly
addresses key performance issues, challenges and techniques for live virtual machine migration in cloud
computing. It also focuses on the key issues related to these existing live virtual machine migration techniques
and summarizes them.
Keywords: Cloud Computing, Migration, Virtualization, Virtual Machine, Physical Machine, Resource
Management, Live Virtual Machine Migration.
1. Introduction
Because of the advancement in Information and Communication Technology (ICT) over past few years,
Computing has been considered as a utility like water, electricity, gas and telephony. These utilities are available
at any time to the consumers based on their requirement. Consumers pay service providers based on their usage
[1] [2] [3] [4].
Like all the other existing utilities, Computing utility is the basic computing service that meets the day to day
needs of the general community. To deliver this vision, a number of computing paradigms have been proposed,
of which the latest one is known as Cloud Computing. Cloud is nothing but large pool of easily accessible and
usable virtual resources [2] [3] [4] [5].
Dr. Rajkumar Buyya says “A Cloud is a type of parallel and distributed system consisting of a collection of
inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified
computing resource(s) based on service-level agreements established through negotiation between the service
provider and consumers.” [3]
In cloud computing various cloud consumers demand variety of services as per their dynamically changing needs.
So it is the job of cloud computing to avail all the demanded services to the cloud consumers. But due to the
availability of finite resources it is very difficult for cloud providers to provide all the demanded services in time.
From the cloud providers’ perspective cloud resources must be allocated in a fair manner. So, it’s a vital issue to
meet cloud consumers’ QoS requirements and satisfaction. The ultimate goal of efficient resource utilization in
cloud computing is to maximize the profit for cloud providers and to minimize the cost for cloud consumers.
Traditional resource allocation techniques are not adequate for cloud computing as it is based on virtualization
technology with distributed nature. Cloud computing introduces new challenges for manageable and flexible
resource allocation due to heterogeneity in hardware capabilities, workload estimation and characteristics in
order to meet Service Level Objectives of the cloud consumers’ applications.
Virtualization itself can be one of the solutions to provide resources to the cloud consumers efficiently by
running multiple VMs on top of single physical host. The term “virtualization” refers to the sharing of same
physical host across multiple concurrently running OS instances. Virtualization mainly abstracts the resources
like CPU and Memory through Virtual Machine for efficient resource utilization [8][14]. Virtualization
multiplexes computing resources on a single cloud platform.
Virtual Machine has been a research topic since past few years as it is independent of hardware implementation
and configurations. Migration is the process of transferring VM from one physical host to another physical host.
If the same can be achieved without interrupting its execution then it is said to be “live”. Live Virtual Machine
2. Computer Engineering and Intelligent Systems www.iiste.org
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Migration is one of the key technique for dynamic resource management in cloud computing [8][14].
The rest of the paper is organized as follows: Section II discusses various live virtual machine migration
techniques proposed by researchers’. Section III gives summary of all these live virtual machine migration
techniques with their used tools and possible improvements. Section IV presents conclusion and discussion on
live virtual machine migration techniques.
2. Literature Survey and Related Work
Sujesha Sudevalayam and Purushottam Kulkarni [9] argued that network affinity-awareness is required in
resource provisioning for virtual machines. Authors have quantified their work of benchmarking of link network
usage for both Xen and KVM virtualization technologies. Authors have also focused on building affinity-aware
models that can predict expected CPU resource requirements based on its location relative to its communicating
set of virtual machines – upon colocation and dispersion of virtual machines.
Pablo Graubner, Matthias Schmidt and Bernd Freisleben [10] presented a novel approach to virtual machine
consolidation based on energy efficient storage migration and live virtual machine migration. Authors tried to
save energy through virtual machine consolidation in IaaS cloud computing environment. Authors have
implemented the same approach using Eucalyptus which is an open source clone of the Amazon Elastic Compute
Cloud (Amazon EC2).
Tiago C. Ferreto, Marco A. S. Netto, Rodrigo N. Calheiros and Cesar A.F. De Rose [11] a new approach
named Dynamic Consolidation with Migration Control. Authors have discussed that current techniques like
static consolidation and dynamic consolidation doesn’t consider the steady usage of virtual machines. Due to
which problems may arise like migration cost and penalty to physical server. So, Authors claimed that for steady
usage migration can be avoided but for variable usage migration can be performed. Authors had used Linear
Programming Formulation and Heuristics approach for the same. Authors had evaluated their proposed approach
with TU-Berlin Workload and Google Workload.
Mayank Mishra, Anwesha Das, Purushottam Kulkarni and Anirudha Sahoo [12] discussed that live virtual
machine migration plays a vital role in dynamic resource management of cloud computing. Authors mainly
focused on efficient resource utilization in non peak periods to minimize wastage of resources. In order to
achieve goals like server consolidation, load balancing and hotspot mitigation, authors discussed three
components – when to migrate, which VM to migrate and where to migrate – and approaches followed by
different heuristics to apply migration techniques. Authors also discussed virtual machine migration over LAN
and WAN with their challenges.
Haikum Liu, Hai Jin, Xiaotei Liao, Chen Yu and Cheng-Zhong Xu [13] had designed, implemented and
evaluated a novel approach that minimises virtual machine migration downtime and network traffic. Authors had
adopted check pointing/recovery and trace/reply technologies for the same and implemented a transparent virtual
machine checkpoint with copy-on-write (COW) mechanism. Authors claimed that their proposed method can be
used in both LAN and WAN. The experimental results showed that a novel approach gives better performance.
Kejiang Ye, Xiaohong Jiang, Dawei Huang, Jianhai Chen and Bei Wang [14] proposed resource reservation
based live migration framework of multiple virtual machines. The target machine in the framework holds four
virtual machines: Migration Decision Maker, Migration Controller, Resource Reservation Controller and
Resource Monitor. Authors focused on improving the migration efficiency through live migration of virtual
machines and proposed three optimization methods: optimization in the source machine, parallel migration of
multiple virtual machines and workload-aware migration strategy. To improve the migration efficiency authors
had considered parameters like downtime, total migration time and workload performance overheads. Authors
claimed that resource reservation strategy is required at source machine and target machine.
Febio Checconi, Tomasso Cucunotta and Manuel Stein [15] addressed real time issues in Live Virtual
Machine Migration. Authors had presented a technique for live migration of real time applications. The main
factor that had been considered by authors is down time of virtual machines due to live migration. Also authors
have introduced probabilistic model for migration process to find out new set of migration policies by building a
sound mathematical theory. Deeper evaluation of the fully implemented proposed technique is still has to be
done by the authors.
3. Summary on Live Virtual Machine Migration Techniques
Table 1 summarizes the work done by various researchers and future work and/or gaps in their existing work.
3. Computer Engineering and Intelligent Systems www.iiste.org
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Table 1 Summary on Live Virtual Machine Migration Techniques
Year Author Techniques/Algorithms
Tools and/or
workload
used
Future work and/or gaps in existing
technologies
2013
Sujesha Sudevalayam and
Purushottam Kulkarni [9]
Affinity aware modelling
of CPU usage with
communicating VMs
Xen and
KVM
Heterogeneity of PMs are not
considered. Benchmarking of 100
Mbps link network usage is done (1
Gbps – not done)
2013
Pablo Graubner, Matthias
Schmidt and Bernd
Freisleben [10]
VM consolidation through
energy efficient storage
migration and live VM
migration
Eucalyptus
Resource management at higher layer
and overhead VM live migrations.
Year Author Techniques/Algorithms
Tools and/or
workload
used
Future work and/or gaps in existing
technologies
2011
Tiago C. Ferreto, Marco A.
S. Netto, Rodrigo N.
Calheiros and Cesar A.F.
De Rose [11]
Dynamic Server
Consolidation with
Migration Control
TU-Berlin
and Google
Workload
Can easily be implemented on
VMWare and Citrix Tools.
2012
Mayank Mishra, Anwesha
Das, Purushottam Kulkarni
and Anirudha Sahoo [12]
Live Virtual Machine
Migration
Not
Mentioned
Only load on the virtual machine for
migration is considered. Consumer
requirements and priority of job is not
considered.
2011
Haikum Liu, Hai Jin,
Xiaotei Liao, Chen Yu and
Cheng-Zhong Xu [13]
Virtual Machine
Checkpoint with copy-on-
write mechanism.
On LAN and
WAN
Multiprocessor virtual machine
migration and design a hybrid scheme
that can apply heuristics to choose
alternative algorithm between precopy
and proposed method.
2011
Kejiang Ye, Xiaohong
Jiang, Dawei Huang,
Jianhai Chen and Bei
Wang [14]
Live Migration of Virtual
Machines
Xen and
VMWare
Intelligent live migration machine can
be future work.
2009
Febio Checconi, Tomasso
Cucunotta and Manuel
Stein [15]
Real Time Issues in Live
Virtual Machine Migration
(new set of migration
policies)
KVM
Deeper evaluation of the fully
implemented proposed technique is
still has to be done by the authors.
4. Conclusion and Discussion
Cloud Computing is the new era of computing for delivering computing as a resource over the today’s internet
world. The success and beauty behind cloud computing is due to the cloud services provided with the cloud over
the internet. Due to the availability of finite resources, it is very important for cloud providers to manage and
assign all the resources in time to cloud consumers as their requirements are changing dynamically.
Live Virtual Machine Migration is one of the key notions for efficient dynamic resource management. Many
authors have proposed algorithms and methods for Live Virtual Machine Migration. In summary, all the authors
tried to achieve very low and predictable downtimes. They also tried to avail resources to the cloud consumers
during migration process.
References
[1] Peter Mell, Timothy Grance, “The NIST Definition of Cloud Computing (Draft)” in Computer Security
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Nirma
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