Scalability refers to the ability to expand cloud facilities and services on demand to meet user needs, beyond any limits. Fault tolerance is the ability to tolerate mistakes made by users. Developing cloud systems that can scale highly and tolerate failures is challenging for cloud providers, as they must manage huge numbers of resources and users while providing competitive performance even as failures occur normally.
This article proposes a system-level approach to providing fault tolerance as a service in cloud computing environments. The key aspects are:
1) A resource manager monitors resources in the cloud and maintains a database and graph representing the state of nodes, VMs, and network links. This provides visibility of resources for managing fault tolerance.
2) Fault tolerance units (ft-units) implement generic fault tolerance mechanisms that can be applied transparently to VMs hosting applications. Examples include replication and failure detection ft-units.
3) A two-stage process first analyzes client requirements and matches them to available ft-units, then deploys the solution by combining suitable ft-units at runtime to provide the desired fault
This document discusses using an Enterprise Service Bus (ESB) architecture as an interoperability and resource sharing platform in the cloud. It describes the need for cloud interoperability and discusses current challenges and efforts related to data/semantic interoperability and customer lock-in. The document proposes using a service bus with light-weight bindings to provide location decoupling and integration of applications and platforms across different cloud providers in a standardized way. Key aspects of the proposed architecture include a virtualization layer, service repository/registry, and composable middleware.
Energy efficient resource allocation in cloud computingDivaynshu Totla
This document discusses energy efficiency in cloud computing. It first provides background on the rising energy consumption of data centers due to increased cloud usage. It then discusses various approaches for improving energy efficiency in clouds, including virtualization and energy-aware scheduling algorithms like round-robin and first-come first-serve. The document proposes an energy-aware VM scheduler that uses these algorithms to minimize server usage and reduce energy consumption while meeting performance requirements. Overall the document analyzes the problem of high cloud energy usage and proposes a scheduler to improve efficiency through virtualization and algorithmic approaches.
This document discusses scheduling in cloud computing environments and summarizes an experimental study comparing different task scheduling policies in virtual machines. It begins with introductions to cloud computing, architectures, and virtualization. It then presents the problem statement of improving application performance under varying resource demands through efficient scheduling. The document outlines simulations conducted using the CloudSim toolkit to evaluate scheduling algorithms like shortest job first, round robin, and a proposed algorithm incorporating machine processing speeds. It presents the implementation including a web interface and concludes that round robin scheduling distributes jobs equally but can cause fragmentation, while the proposed algorithm aims to overcome limitations of existing approaches.
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
Cloud computing architecture and vulnerabiliesVinay Dwivedi
The document discusses key aspects of cloud computing including its evolution, architecture, characteristics, security issues, and requirements. Specifically, it outlines the need for cloud computing, defines cloud computing and service-oriented architecture, describes the technical and conceptual characteristics of clouds, and identifies important security considerations like identification, authorization, confidentiality and integrity.
A Survey on Resource Allocation & Monitoring in Cloud ComputingMohd Hairey
This document provides an overview of a survey on resource allocation and monitoring in cloud computing. It discusses (1) cloud computing and its key characteristics, (2) elements of resource management including allocation, monitoring, discovery and provisioning, (3) existing mechanisms for resource allocation and monitoring, and (4) gaps in current approaches. The survey aims to study resource allocation and monitoring in cloud computing and describe issues and current solutions to help develop a better resource management framework.
Scalability refers to the ability to expand cloud facilities and services on demand to meet user needs, beyond any limits. Fault tolerance is the ability to tolerate mistakes made by users. Developing cloud systems that can scale highly and tolerate failures is challenging for cloud providers, as they must manage huge numbers of resources and users while providing competitive performance even as failures occur normally.
This article proposes a system-level approach to providing fault tolerance as a service in cloud computing environments. The key aspects are:
1) A resource manager monitors resources in the cloud and maintains a database and graph representing the state of nodes, VMs, and network links. This provides visibility of resources for managing fault tolerance.
2) Fault tolerance units (ft-units) implement generic fault tolerance mechanisms that can be applied transparently to VMs hosting applications. Examples include replication and failure detection ft-units.
3) A two-stage process first analyzes client requirements and matches them to available ft-units, then deploys the solution by combining suitable ft-units at runtime to provide the desired fault
This document discusses using an Enterprise Service Bus (ESB) architecture as an interoperability and resource sharing platform in the cloud. It describes the need for cloud interoperability and discusses current challenges and efforts related to data/semantic interoperability and customer lock-in. The document proposes using a service bus with light-weight bindings to provide location decoupling and integration of applications and platforms across different cloud providers in a standardized way. Key aspects of the proposed architecture include a virtualization layer, service repository/registry, and composable middleware.
Energy efficient resource allocation in cloud computingDivaynshu Totla
This document discusses energy efficiency in cloud computing. It first provides background on the rising energy consumption of data centers due to increased cloud usage. It then discusses various approaches for improving energy efficiency in clouds, including virtualization and energy-aware scheduling algorithms like round-robin and first-come first-serve. The document proposes an energy-aware VM scheduler that uses these algorithms to minimize server usage and reduce energy consumption while meeting performance requirements. Overall the document analyzes the problem of high cloud energy usage and proposes a scheduler to improve efficiency through virtualization and algorithmic approaches.
This document discusses scheduling in cloud computing environments and summarizes an experimental study comparing different task scheduling policies in virtual machines. It begins with introductions to cloud computing, architectures, and virtualization. It then presents the problem statement of improving application performance under varying resource demands through efficient scheduling. The document outlines simulations conducted using the CloudSim toolkit to evaluate scheduling algorithms like shortest job first, round robin, and a proposed algorithm incorporating machine processing speeds. It presents the implementation including a web interface and concludes that round robin scheduling distributes jobs equally but can cause fragmentation, while the proposed algorithm aims to overcome limitations of existing approaches.
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
Cloud computing architecture and vulnerabiliesVinay Dwivedi
The document discusses key aspects of cloud computing including its evolution, architecture, characteristics, security issues, and requirements. Specifically, it outlines the need for cloud computing, defines cloud computing and service-oriented architecture, describes the technical and conceptual characteristics of clouds, and identifies important security considerations like identification, authorization, confidentiality and integrity.
A Survey on Resource Allocation & Monitoring in Cloud ComputingMohd Hairey
This document provides an overview of a survey on resource allocation and monitoring in cloud computing. It discusses (1) cloud computing and its key characteristics, (2) elements of resource management including allocation, monitoring, discovery and provisioning, (3) existing mechanisms for resource allocation and monitoring, and (4) gaps in current approaches. The survey aims to study resource allocation and monitoring in cloud computing and describe issues and current solutions to help develop a better resource management framework.
Cloud computing is a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications.
In cloud computing, the word cloud (also phrased as "the cloud") is used as a metaphor for "the Internet," so the phrase cloud computing means "a type of Internet-based computing," where different services — such as servers, storage and applications — are delivered to an organization's computers and devices through the Internet.
Grid computing allows for the sharing of computer resources across a network. It utilizes both reliable tightly-coupled cluster resources as well as loosely-coupled unreliable machines. The grid system balances resource usage to provide quality of service to participants. Grid computing works by having at least one administrative computer and middleware that allows computers on the network to share processing power and data storage. It has advantages like improved efficiency, resilience, and ability to handle large applications, but also challenges around resource sharing and licensing across multiple servers.
State of Public Sector Cloud Computing 2010Victor Gridnev
This document provides an overview of cloud computing initiatives across the public sector. It defines cloud computing and outlines the Federal Government's approach, including defining cloud computing, pursuing data center consolidation, developing standards, and planning budgets to foster cloud adoption. The document also presents 30 case studies of cloud computing implementations at various government agencies and jurisdictions to illustrate the growing adoption of cloud technologies across the public sector.
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
The Grid means the infrastructure for the Advanced Web, for computing, collaboration and communication.
The goal is to create the illusion of a simple yet large and powerful self managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources.
“Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and ,in some cases, high-performance orientation .
We presented the Grid concept in analogy with that of an electrical power grid and Grid vision
35 content distribution with dynamic migration of services for minimum cost u...INFOGAIN PUBLICATION
Content Delivery Networks are the key for today’s internet content delivery. Users are knowingly or unknowingly accessing the CDN via internet. No matter how much the data retrieved by the user it may contain the CDN hand behind every character of text and every pixel of image. CDN came into existence to solve the delay problem. The moment when a user requests for a web page and the response delivered to the corresponding users web browser facing a huge delay. The main goal of this paper is content distribution of web services to multiple data centers placed in different geographical locations and providing security. A content distribution service is a major part of popular Internet applications. In proposed system hybrid clouds are used i.e., both private cloud as well as public cloud. One data center is allocated to each region. Providing security to the data is always an important issue because of the critical nature of the cloud and very large amount of complicated data it carries. To provide security cipher text policy algorithm is used. Authentication technique is used to verify the user authentication. If the user is authorized to access services then and only he receives configuration key to use.
This document summarizes a thesis submitted to Punjabi University for a Master of Technology degree in Computer Sciences and Engineering. The thesis, written by Kirandeep Kaur and supervised by Dr. Rajesh K. Bawa, proposes a novel flexible resource scheduling model for public clouds to avoid resource starvation. It introduces the problem of resource starvation in cloud computing environments and reviews existing resource scheduling mechanisms. The proposed model aims to simulate a public cloud environment using CloudSim and demonstrate that no user request will starve without proper resource allocation through a flexible scheduling approach that considers server load.
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
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.
The past decade has seen increasingly ambitious and successful methods for outsourcing computing. Approaches such as utility computing, on-demand computing, grid computing, software as a service, and cloud computing all seek to free computer applications from the limiting confines of a single computer. Software that thus runs "outside the box" can be more powerful (think Google, TeraGrid), dynamic (think Animoto, caBIG), and collaborative (think FaceBook, myExperiment). It can also be cheaper, due to economies of scale in hardware and software. The combination of new functionality and new economics inspires new applications, reduces barriers to entry for application providers, and in general disrupts the computing ecosystem. I discuss the new applications that outside-the-box computing enables, in both business and science, and the hardware and software architectures that make these new applications possible.
i-softinc is a one of the most popular development company for developing android application development in USA. It is a leading company which provides best services for android app development services in USA. Today, i-softinc has developed 1000+ apps and 250+ happy clients across the world. There are so many companies for developing mobile application Development Company in USA. Among all companies, I-Softinc is a top most development company for developing best mobile application development in USA. The professional and expert of i-softinc always develop and design best mobile application Development Company in USA.
The document discusses cloud service life-cycle management and related topics. It covers (1) the cloud service life-cycle including requirements, discovery, negotiation, composition, and consumption phases, (2) high-level cloud deployment scenarios such as single cloud system, multiple cloud systems serially or simultaneously, (3) tools for cloud service development and testing including NetBeans, Eclipse, Apache JMeter, and SoapUI, and (4) the concept of web service slicing to capture a functional subset of a large-scale web service for regression testing purposes.
This document provides an overview of cloud computing, including its history, key concepts, architecture, deployment models, service models, virtualization, scheduling, and security. Cloud computing allows for on-demand access to shared computing resources over the internet. There are four deployment models (public, private, hybrid, community) and three main service models (SaaS, PaaS, IaaS). Virtualization is a core technology that allows efficient sharing of physical resources. Scheduling algorithms are used to allocate and deliver virtual resources. Security challenges include threats to data, interfaces, and system vulnerabilities.
1. The document discusses the economic properties of cloud computing including common infrastructure, location independence, online connectivity, utility pricing, and on-demand resources.
2. It provides details on utility pricing models and how cloud computing can be cheaper than owning resources depending on the ratio of peak to average demand.
3. On-demand cloud resources allow organizations to dynamically scale up or down based on changing demand levels without penalty, which provides significant economic benefits over static resource provisioning.
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
E VALUATION OF T WO - L EVEL G LOBAL L OAD B ALANCING F RAMEWORK IN C L...ijcsit
With technological advancements and c
onstant changes of Internet, cloud computing has been today's
trend. With the lower cost and convenience of cloud computing services, users have increasingly put
their
Web resources and information in the cloud environment. The availability and reliability
of the client
systems will become increasingly important. Today cloud applications slightest interruption, the imp
act
will be significant for users. It is an important issue that how to ensure reliability and stability
of the cloud
sites. Load balancing w
ould be one good solution.
This paper presents a framework for global server load balancing of the Web sites in a cloud with tw
o
-
level
load balancing model. The proposed framework is intended for adapting an open
-
source load
-
balancing
system and the frame
work allows the network service provider to deploy a load balancer in different data
centers dynamically while the customers need more load balancers for increasing the availability
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.
This document discusses cloud computing concepts including its key characteristics, service models, and deployment models. Cloud computing refers to applications and services delivered over the internet using shared computing resources. The main advantages of cloud computing are no upfront investment in servers or software, flexibility, scalability, and pay-per-use models. The three service models are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). The four deployment models are private cloud, public cloud, hybrid cloud, and community cloud. Security and programmability are ongoing challenges that cloud computing aims to address through standardization.
This document provides an overview of cloud computing concepts including objectives, course outcomes, and syllabus details. The objectives are to understand cloud computing concepts, evolution, issues, key players, and its emergence as the next generation computing paradigm. The course outcomes include being able to articulate cloud concepts, technologies, architectures, issues like resource management and security, and evaluate appropriate technologies. The syllabus covers topics like introduction, enabling technologies, architecture, services, storage, resource management, security, technologies and advancements.
This document provides an overview of ANEKA, a cloud application platform developed by Manjrasoft Pvt. Ltd. that allows for building and managing distributed applications and multiple clouds. It discusses cloud computing concepts and the need for multiple clouds and resource management. ANEKA addresses issues with existing approaches by providing programming models, tools, and APIs to deploy scalable applications across distributed networks and clouds. The document outlines ANEKA's architecture, functions for building, deploying, and managing applications, and compares its programming models including Task, Thread, MapReduce, and Parameter Sweeping. In summary, ANEKA is a platform that enables development of applications for multiple cloud environments and distributed networks through its programming abstractions and
This document summarizes challenges with migrating applications between cloud environments and discusses potential solutions. It addresses three main points:
1) Application architecture impacts migration ability, and architectures like asynchronous apps are better suited for cloud portability.
2) Standards like OVF could help by providing universal metadata for virtual machines, but full standards adoption will take time.
3) Tools to automate migration are needed to move apps without rewriting them for each cloud, but current tools often result in multiple versions that are difficult to manage.
Cloud computing is a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications.
In cloud computing, the word cloud (also phrased as "the cloud") is used as a metaphor for "the Internet," so the phrase cloud computing means "a type of Internet-based computing," where different services — such as servers, storage and applications — are delivered to an organization's computers and devices through the Internet.
Grid computing allows for the sharing of computer resources across a network. It utilizes both reliable tightly-coupled cluster resources as well as loosely-coupled unreliable machines. The grid system balances resource usage to provide quality of service to participants. Grid computing works by having at least one administrative computer and middleware that allows computers on the network to share processing power and data storage. It has advantages like improved efficiency, resilience, and ability to handle large applications, but also challenges around resource sharing and licensing across multiple servers.
State of Public Sector Cloud Computing 2010Victor Gridnev
This document provides an overview of cloud computing initiatives across the public sector. It defines cloud computing and outlines the Federal Government's approach, including defining cloud computing, pursuing data center consolidation, developing standards, and planning budgets to foster cloud adoption. The document also presents 30 case studies of cloud computing implementations at various government agencies and jurisdictions to illustrate the growing adoption of cloud technologies across the public sector.
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
The Grid means the infrastructure for the Advanced Web, for computing, collaboration and communication.
The goal is to create the illusion of a simple yet large and powerful self managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources.
“Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and ,in some cases, high-performance orientation .
We presented the Grid concept in analogy with that of an electrical power grid and Grid vision
35 content distribution with dynamic migration of services for minimum cost u...INFOGAIN PUBLICATION
Content Delivery Networks are the key for today’s internet content delivery. Users are knowingly or unknowingly accessing the CDN via internet. No matter how much the data retrieved by the user it may contain the CDN hand behind every character of text and every pixel of image. CDN came into existence to solve the delay problem. The moment when a user requests for a web page and the response delivered to the corresponding users web browser facing a huge delay. The main goal of this paper is content distribution of web services to multiple data centers placed in different geographical locations and providing security. A content distribution service is a major part of popular Internet applications. In proposed system hybrid clouds are used i.e., both private cloud as well as public cloud. One data center is allocated to each region. Providing security to the data is always an important issue because of the critical nature of the cloud and very large amount of complicated data it carries. To provide security cipher text policy algorithm is used. Authentication technique is used to verify the user authentication. If the user is authorized to access services then and only he receives configuration key to use.
This document summarizes a thesis submitted to Punjabi University for a Master of Technology degree in Computer Sciences and Engineering. The thesis, written by Kirandeep Kaur and supervised by Dr. Rajesh K. Bawa, proposes a novel flexible resource scheduling model for public clouds to avoid resource starvation. It introduces the problem of resource starvation in cloud computing environments and reviews existing resource scheduling mechanisms. The proposed model aims to simulate a public cloud environment using CloudSim and demonstrate that no user request will starve without proper resource allocation through a flexible scheduling approach that considers server load.
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
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.
The past decade has seen increasingly ambitious and successful methods for outsourcing computing. Approaches such as utility computing, on-demand computing, grid computing, software as a service, and cloud computing all seek to free computer applications from the limiting confines of a single computer. Software that thus runs "outside the box" can be more powerful (think Google, TeraGrid), dynamic (think Animoto, caBIG), and collaborative (think FaceBook, myExperiment). It can also be cheaper, due to economies of scale in hardware and software. The combination of new functionality and new economics inspires new applications, reduces barriers to entry for application providers, and in general disrupts the computing ecosystem. I discuss the new applications that outside-the-box computing enables, in both business and science, and the hardware and software architectures that make these new applications possible.
i-softinc is a one of the most popular development company for developing android application development in USA. It is a leading company which provides best services for android app development services in USA. Today, i-softinc has developed 1000+ apps and 250+ happy clients across the world. There are so many companies for developing mobile application Development Company in USA. Among all companies, I-Softinc is a top most development company for developing best mobile application development in USA. The professional and expert of i-softinc always develop and design best mobile application Development Company in USA.
The document discusses cloud service life-cycle management and related topics. It covers (1) the cloud service life-cycle including requirements, discovery, negotiation, composition, and consumption phases, (2) high-level cloud deployment scenarios such as single cloud system, multiple cloud systems serially or simultaneously, (3) tools for cloud service development and testing including NetBeans, Eclipse, Apache JMeter, and SoapUI, and (4) the concept of web service slicing to capture a functional subset of a large-scale web service for regression testing purposes.
This document provides an overview of cloud computing, including its history, key concepts, architecture, deployment models, service models, virtualization, scheduling, and security. Cloud computing allows for on-demand access to shared computing resources over the internet. There are four deployment models (public, private, hybrid, community) and three main service models (SaaS, PaaS, IaaS). Virtualization is a core technology that allows efficient sharing of physical resources. Scheduling algorithms are used to allocate and deliver virtual resources. Security challenges include threats to data, interfaces, and system vulnerabilities.
1. The document discusses the economic properties of cloud computing including common infrastructure, location independence, online connectivity, utility pricing, and on-demand resources.
2. It provides details on utility pricing models and how cloud computing can be cheaper than owning resources depending on the ratio of peak to average demand.
3. On-demand cloud resources allow organizations to dynamically scale up or down based on changing demand levels without penalty, which provides significant economic benefits over static resource provisioning.
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
E VALUATION OF T WO - L EVEL G LOBAL L OAD B ALANCING F RAMEWORK IN C L...ijcsit
With technological advancements and c
onstant changes of Internet, cloud computing has been today's
trend. With the lower cost and convenience of cloud computing services, users have increasingly put
their
Web resources and information in the cloud environment. The availability and reliability
of the client
systems will become increasingly important. Today cloud applications slightest interruption, the imp
act
will be significant for users. It is an important issue that how to ensure reliability and stability
of the cloud
sites. Load balancing w
ould be one good solution.
This paper presents a framework for global server load balancing of the Web sites in a cloud with tw
o
-
level
load balancing model. The proposed framework is intended for adapting an open
-
source load
-
balancing
system and the frame
work allows the network service provider to deploy a load balancer in different data
centers dynamically while the customers need more load balancers for increasing the availability
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.
This document discusses cloud computing concepts including its key characteristics, service models, and deployment models. Cloud computing refers to applications and services delivered over the internet using shared computing resources. The main advantages of cloud computing are no upfront investment in servers or software, flexibility, scalability, and pay-per-use models. The three service models are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). The four deployment models are private cloud, public cloud, hybrid cloud, and community cloud. Security and programmability are ongoing challenges that cloud computing aims to address through standardization.
This document provides an overview of cloud computing concepts including objectives, course outcomes, and syllabus details. The objectives are to understand cloud computing concepts, evolution, issues, key players, and its emergence as the next generation computing paradigm. The course outcomes include being able to articulate cloud concepts, technologies, architectures, issues like resource management and security, and evaluate appropriate technologies. The syllabus covers topics like introduction, enabling technologies, architecture, services, storage, resource management, security, technologies and advancements.
This document provides an overview of ANEKA, a cloud application platform developed by Manjrasoft Pvt. Ltd. that allows for building and managing distributed applications and multiple clouds. It discusses cloud computing concepts and the need for multiple clouds and resource management. ANEKA addresses issues with existing approaches by providing programming models, tools, and APIs to deploy scalable applications across distributed networks and clouds. The document outlines ANEKA's architecture, functions for building, deploying, and managing applications, and compares its programming models including Task, Thread, MapReduce, and Parameter Sweeping. In summary, ANEKA is a platform that enables development of applications for multiple cloud environments and distributed networks through its programming abstractions and
This document summarizes challenges with migrating applications between cloud environments and discusses potential solutions. It addresses three main points:
1) Application architecture impacts migration ability, and architectures like asynchronous apps are better suited for cloud portability.
2) Standards like OVF could help by providing universal metadata for virtual machines, but full standards adoption will take time.
3) Tools to automate migration are needed to move apps without rewriting them for each cloud, but current tools often result in multiple versions that are difficult to manage.
1) The document proposes a bandwidth-aware virtual machine migration policy for cloud data centers that considers both the bandwidth and computing power of resources when scheduling tasks of varying sizes.
2) It presents an algorithm that binds tasks to virtual machines in the current data center if the load is below the saturation threshold, and migrates tasks to the next data center if the load is above the threshold, in order to minimize completion time.
3) Experimental results show that the proposed algorithm has lower completion times compared to an existing single data center scheduling algorithm, demonstrating the benefits of considering bandwidth and utilizing multiple data centers.
Cost-Minimizing Dynamic Migration of Content Distribution Services into Hybri...nexgentechnology
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Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
COST-MINIMIZING DYNAMIC MIGRATION OF CONTENT DISTRIBUTION SERVICES INTO HYBR...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Cost minimizing dynamic migration of contentnexgentech15
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
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Methodologies for Enhancing Data Integrity and Security in Distributed Cloud ...IIJSRJournal
Usually, cloud infrastructure is used individually by businesses, whereas the hybrid cloud would be a blend of two or many kinds of clouds. Because as clouds become increasingly common, safety issues also expanding. Because of such cybersecurity threats, numerous experts suggested procedures as well as ways to assure internet confidentiality. Providers of cloud-based services were accountable for the complete safety of cloud information. Nevertheless, since the clouds are accessible (easily accessible over the World wide web), much research has been conducted on cloud storage cybersecurity. This paper describes methods for enhancing security and reliability in decentralized cloud-based solutions, as well as suggests a few security solution methods of implementation.
Dynamic Resource Provisioning with Authentication in Distributed DatabaseEditor IJCATR
Data center have the largest consumption amounts of energy in sharing the power. The public cloud workloads of different
priorities and performance requirements of various applications [4]. Cloud data center have capable of sensing an opportunity to present
different programs. In my proposed construction and the name of the security level of imperturbable privacy leakage rarely distributed
cloud system to deal with the persistent characteristics there is a substantial increases and information that can be used to augment the
profit, retrenchment overhead or both. Data Mining Analysis of data from different perspectives and summarizing it into useful
information is a process. Three empirical algorithms have been proposed assignments estimate the ratios are dissected theoretically and
compared using real Internet latency data recital of testing methods
This document provides 6 IEEE project summaries in the domain of Java and cloud computing/data mining. The summaries are:
1. A decentralized access control scheme for secure cloud data storage that supports anonymous authentication.
2. A performance analysis framework for distributed file systems that qualitatively and quantitatively evaluates performance.
3. Approaches to guarantee trustworthy transactions on cloud servers by enforcing policy consistency constraints.
4. A scalable MapReduce approach for anonymizing large datasets to satisfy privacy requirements like k-anonymity.
5. A resource allocation scheme for a self-organizing cloud that achieves maximized utilization and optimal execution efficiency.
6. An attribute-based encryption framework for flexible
This document discusses cloud computing concepts and applications in a military context. It defines cloud computing and describes common cloud themes like scalability, on-demand access, and location independence. It outlines business benefits like automation, data intensive computing, and accessibility from any device. The document also discusses DISA's focus on infrastructure/platform capabilities and lists several of DISA's cloud-related efforts.
Cloud computing is a technique that has a great capabilities and benefits for users. Cloud characteristics
encourage many organizations to move to this technology. But many consideration faces transmission
process. This paper outline some of these considerations and considerable efforts solved cloud scalability
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Contemporary Energy Optimization for Mobile and Cloud Environmentijceronline
Cloud and mobile computing applications are increasing heavily in terms of usage. These two areas extending usability of systems. This review paper gives information about cloud and mobile applications in terms of resources they consume and the need of choosing variety of features for users from several locations and the evolutionary provisions for service provider and end users. Both the fields are combined to provide good functionality, efficiency and effectiveness with mobile phones. The enhancement by considering power consumption by means of resource constrained nature of devices, communication media and cost effectiveness. This paper discuss about the concepts related to power consumption, underlying protocols and the other performance issues
ANALYSIS OF THE COMPARISON OF SELECTIVE CLOUD VENDORS SERVICESijccsa
Cloud computing refers to a location that allows us to preserve our precious data and use computing and
networking services on a pay-as-you-go basis without the need for a physical infrastructure. Cloud
computing now provides us with powerful data processing and storage, exceptional availability and
security, rapid accessibility and adaption, ensured flexibility and interoperability, and time and cost
efficiency. Cloud computing offers three platforms (IaaS, PaaS, and SaaS) with unique capabilities that
promise to make it easier for a customer, organization, or trade to establish any type of IT business. We
compared a variety of cloud service characteristics in this article, following the comparing, it's
straightforward to pick a specific cloud service from the possible options by comparison with three chosen
cloud providers such as Amazon, Microsoft Azure, and Digital Ocean. By using findings of this study to not
only identify similarities and contrasts across various aspects of cloud computing, as well as to suggest
some areas for further study.
Migration to cloud is no easy task. Start small and learn the core technologies before leveraging the advanced features of the cloud. The cultural change will affect the whole organization from development to business management and sales.
Cloud native applications are the future of software. Modern software is stateless, provided from cloud to heterogeneous clients on demand and designed to be scalable and resilient.
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.
Introduction to Cloud Computing(UNIT 1).pptxSURBHI SAROHA
This document provides an introduction to cloud computing, including definitions, characteristics, service models, deployment models, and virtualization concepts. It defines cloud computing as storing and accessing data and programs on remote servers hosted on the internet. The main service models are infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). The primary deployment models are public cloud, private cloud, hybrid cloud, community cloud, and multi-cloud. Virtualization allows for the sharing of physical resources and is key to cloud computing.
Now a days the work is being done by hiring the space and resources from the cloud providers in order to do work effectively and less costly. This paper describes the cloud, its challenges, evolution, attacks along with the approaches required to handle data on cloud. The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer. The need of this review paper is to provide the awareness of the current emerging technology which saves the cost of users.
The document discusses several topics related to cloud computing including:
1. A hybrid cloud approach for secure authorized data deduplication that considers differential user privileges.
2. A framework called AMES-Cloud that provides adaptive mobile video streaming and efficient social video sharing using private cloud agents.
3. Research into using multi-cloud providers instead of single clouds to help maintain security.
Private Cloud With System Center ProjectAbhijit Kundu
The document provides an overview of creating a private cloud using Microsoft System Center 2012, including an introduction to private clouds and their benefits, an overview of the key System Center 2012 components used to create and manage a private cloud, and prerequisites for installing a private cloud such as required virtual machines, software, and physical server configurations.
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Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
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Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
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Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
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Programming Foundation Models with DSPy - Meetup SlidesZilliz
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5th Power Grid Model Meet-up
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Power Grid Model
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What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
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-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
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Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
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3. INTRODUCTION
Cloud computing is a type of computing that relies
on sharing computing resources to handle
applications.
Load balancing in cloud environment is one of the
critical issue while processing and storing the
various multimedia application at the same time.
Cloud based multimedia system offers services of
generating, editing, processing of multimedia data
4. OBJECTIVES
To distribute the cloud data for more users at the same
time
Client can get the data without any interruptions.
To minimize the cost for transmitting multimedia data
between server clusters and clients
5. LITERATURE REVIEW
S.No Paper Title Publicatio
n details
Proposed
work
Merits Demerits
1 Dynamic
Multi-Service
Load Balancing in
Cloud-based
Multimedia
System
May 2013 in
IEEE
Transaction
To increase
the load
balancing
efficiency for
Cloud
Multimedia
files
Load
balancing
for all
multimedia
service tasks
are of the
same type is
maintained
Inability to
consider load
balancing
should adapt
to time
change in
dynamic
scenario
2 Multi-service
Load Balancing in
a Heterogeneous
Network with
Vertical Handover
November
2008 in
Springer
To overlay
heterogeneou
s
WiMAX/WL
AN network
thro’ vertical
handover
To improve
the
performance
of handover
user
Load
balancing in
WiMAX6
affect the
whole system
performance
6. PROPOSED SYSTEM
Huge number of clients request for different
Multimedia services through internet .
To implement a centralized Cloud-based Multimedia
System(CMS), we proposed a genetic algorithm for
concerned dynamic load balancing problem in CMS.
7. PROPOSED SYSTEM
The resource manager of CMS stores the global
service task load information collected from server
clusters
Decides the amount of client’s requests assigned to
each server cluster.
Then the load of each server cluster is distributed as
balanced as possible
8. GENETIC ALGORITHM
Solution to a problem solved by genetic algorithms, is
evolved
Algorithm is started with a set of solution
(represented by chromosomes) called Population
Solutions from one population are taken and used to
form a new population for a better one.
9. GENETIC ALGORITHM
Solutions which are selected to form new solutions
(offspring) are selected according to their fitness
function
The most suitable one will got more chances and
they have to reproduce
Repeated until some condition is satisfied.
13. MODULE DESCRIPTION
File upload module
-Admin upload all Multimedia files.
-Determine file path
- stored in the Cloud Server.
14. MODULE DESCRIPTION
Service requestor module
-User request a multimedia file to the Resource
Manager
-It assign the request to cloud server
15. APPLICATION
Cloud Service Oriented Applications
-Organized as object and they communicate
between the servers and collaborate over the network
Online Multimedia Tools and Application
-multiple media components are combined and
work together
16. CONCLUSION
In cloud paradigm the effective resource utilization is
required for achieving user satisfaction
Maximizing the profit for cloud service providers.
17. FUTURE ENHANCEMENT
As a future work we extend the behavioral
characterization of proximity malware to account for
strategic malware detection evasion with game theory
is a challenging task.
User utilizes the source with no limitation.
It accept certain range of request and once the server
free allows N number of request
18. REFERENCES
Yuming Jiang, Andrew Perkis, “Multi-service Load
Balancing in a Heterogeneous Network with Vertical
Handover,” International Journal of Advanced Research in
Computer and Communication Engineering, vol. 3, Issue.
7, pp. 7359–7362, July. 2014.
C. C. Lin, H. H. Chin, and D. J. Deng, "Dynamic Multi-
Service Load Balancing in Cloud-based Multimedia
System," IEEE System Journal, Vol. 8, Issue 1, pp. 225-
234, 2014.