Cloud Computing :Technologies for Network-Based Systems - System Models for Distributed and Cloud Computing - Implementation Levels of Virtualization - Virtualization Structures/Tools and Mechanisms - Virtualization of CPU, Memory, and I/O Devices - Virtual Clusters and Resource Management - Virtualization for Data-Center Automation.
The document discusses cloud architecture and describes the different layers of cloud computing including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It explains how virtualization allows for the pooling of computing resources and rapid provisioning of these resources. The document also discusses multi-tenancy and how a single software instance can be configured for multiple tenants' needs in a SaaS environment. As an example, it describes how a payroll processing application currently used by multiple government departments could be migrated to a cloud environment for improved maintenance and reduced costs.
The document discusses cloud middleware and various cloud platforms. It provides details about Eucalyptus, OpenStack, Ubuntu Enterprise Cloud, Amazon EC2, Google App Engine, and their components. Eucalyptus is an open-source software for building private and hybrid clouds. It implements Amazon Web Services APIs and interfaces. OpenStack is an open-source cloud platform consisting of modules like Nova, Swift, Glance, Keystone and Horizon. Ubuntu Enterprise Cloud is a commercial version of Eucalyptus that provides tools for managing infrastructure and users. Amazon EC2 and Google App Engine are commercial cloud platforms that allow deploying and scaling web applications.
Cloud computing is the on-demand delivery of IT resources and applications via the Internet with pay-as-you-go pricing. It evolved from earlier technologies like grid computing and utility computing by providing greater ease of use and on-demand scaling. A cloud broker acts as an intermediary between cloud service providers and customers, providing a unified interface and moving workloads between public and private clouds for improved performance and redundancy.
T-Systems is an ICT service provider that offers cloud-based solutions for business applications from its 75 data centers globally. It leverages cloud computing by delivering services from its data centers while ensuring solutions comply with security and legal requirements. T-Systems provides dynamic ICT services through standardized, automated, and modular cloud platforms to help companies launch new services and products flexibly. It offers core cloud computing, storage, and communication modules as well as dynamic applications for enterprises around areas like communications, ERP, development, and devices. One example is how T-Systems provided a flexible private cloud infrastructure service for a furniture manufacturer to scale its IT resources up or down based on seasonal demand changes.
• What is MapReduce?
• What are MapReduce implementations?
Facing these questions I have make a personal research, and realize a synthesis, which has help me to clarify some ideas. The attached presentation does not intend to be exhaustive on the subject, but could perhaps bring you some useful insights.
Virtualization allows multiple operating systems and applications to run on a single server at the same time, improving hardware utilization and flexibility. It reduces costs by consolidating servers and enabling more efficient use of resources. Key benefits of VMware virtualization include easier manageability, fault isolation, reduced costs, and the ability to separate applications.
The document discusses cloud architecture and describes the different layers of cloud computing including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It explains how virtualization allows for the pooling of computing resources and rapid provisioning of these resources. The document also discusses multi-tenancy and how a single software instance can be configured for multiple tenants' needs in a SaaS environment. As an example, it describes how a payroll processing application currently used by multiple government departments could be migrated to a cloud environment for improved maintenance and reduced costs.
The document discusses cloud middleware and various cloud platforms. It provides details about Eucalyptus, OpenStack, Ubuntu Enterprise Cloud, Amazon EC2, Google App Engine, and their components. Eucalyptus is an open-source software for building private and hybrid clouds. It implements Amazon Web Services APIs and interfaces. OpenStack is an open-source cloud platform consisting of modules like Nova, Swift, Glance, Keystone and Horizon. Ubuntu Enterprise Cloud is a commercial version of Eucalyptus that provides tools for managing infrastructure and users. Amazon EC2 and Google App Engine are commercial cloud platforms that allow deploying and scaling web applications.
Cloud computing is the on-demand delivery of IT resources and applications via the Internet with pay-as-you-go pricing. It evolved from earlier technologies like grid computing and utility computing by providing greater ease of use and on-demand scaling. A cloud broker acts as an intermediary between cloud service providers and customers, providing a unified interface and moving workloads between public and private clouds for improved performance and redundancy.
T-Systems is an ICT service provider that offers cloud-based solutions for business applications from its 75 data centers globally. It leverages cloud computing by delivering services from its data centers while ensuring solutions comply with security and legal requirements. T-Systems provides dynamic ICT services through standardized, automated, and modular cloud platforms to help companies launch new services and products flexibly. It offers core cloud computing, storage, and communication modules as well as dynamic applications for enterprises around areas like communications, ERP, development, and devices. One example is how T-Systems provided a flexible private cloud infrastructure service for a furniture manufacturer to scale its IT resources up or down based on seasonal demand changes.
• What is MapReduce?
• What are MapReduce implementations?
Facing these questions I have make a personal research, and realize a synthesis, which has help me to clarify some ideas. The attached presentation does not intend to be exhaustive on the subject, but could perhaps bring you some useful insights.
Virtualization allows multiple operating systems and applications to run on a single server at the same time, improving hardware utilization and flexibility. It reduces costs by consolidating servers and enabling more efficient use of resources. Key benefits of VMware virtualization include easier manageability, fault isolation, reduced costs, and the ability to separate applications.
A quick overview of the possible business models of the cloud computing companies. Done for Tampere University of Technology seminar course about cloud computing ( http://www.cs.tut.fi/~tsysta/Pilvilaskenta.html ).
The document discusses cloud resource management and cloud computing architecture. It covers the following key points in 3 sentences:
Cloud architecture can be broadly divided into the front end, which consists of interfaces and applications for accessing cloud platforms, and the back end, which comprises resources for providing cloud services like storage, virtual machines, and security mechanisms. Common cloud service models include infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Virtualization techniques allow for the sharing of physical resources among multiple organizations by assigning logical names to physical resources and providing pointers to access them.
Cloud computing allows users to access virtual hardware, software, platforms, and services on an as-needed basis without large upfront costs or commitments. This transforms computing into a utility that can be easily provisioned and composed. The long-term vision is for an open global marketplace where IT services are freely traded like utilities, lowering barriers and allowing flexible access to resources and software for all users.
cloud computing, Principle and Paradigms: 1 introdutionMajid Hajibaba
The document is a presentation on cloud computing that covers its principles, paradigms, and various models. It defines cloud computing, discusses its roots in technologies like grid computing and virtualization, and describes the different layers including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It also covers deployment models, desired features, infrastructure management challenges, and examples of cloud providers like Amazon Web Services.
The document discusses cloud computing, providing definitions and an overview of key concepts. It describes the three main cloud service models - Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Examples of applications are given for each model. Advantages of cloud computing include lower costs, automatic software updates, unlimited storage, and collaboration capabilities. However, cloud computing also has disadvantages such as reliance on internet connectivity and potential security and data loss issues.
Introduction to Cloud Computing and Cloud InfrastructureSANTHOSHKUMARKL1
Introduction, Cloud Infrastructure: Cloud computing, Cloud computing delivery models and services, Ethical issues, Cloud vulnerabilities, Cloud computing at Amazon, Cloud computing the Google perspective, Microsoft Windows Azure and online services, Open-source software platforms for private clouds.
A brief discussion about Cloud computing for a beginner, you can get a clear idea about cloud computing from this slides.Also, discuss cloudsim simulator.
Cloud computing & energy efficiency using cloud to decrease the energy use in...Puru Agrawal
Cloud can be used to decrease the energy use in large companies. This presentation deals with a model which explains as how cloud can be used to decrease the energy uses. This is a field related to green computing and minimum use of energy resources.
The document discusses several security challenges related to cloud computing. It covers topics like data breaches, misconfiguration issues, lack of cloud security strategy, insufficient identity and access management, account hijacking, insider threats, and insecure application programming interfaces. The document emphasizes that securing customer data and applications is critical for cloud service providers to maintain trust and meet compliance requirements.
This document provides an overview of different distributed computing models including cluster computing, grid computing, peer-to-peer networks, and cloud computing. It describes key characteristics of each model such as architecture, advantages, disadvantages, and applications. Cluster computing uses interconnected stand-alone computers that work cooperatively, while grid computing consists of distributed systems from different administrative domains. Peer-to-peer networks allow sharing of files directly between nodes without a centralized server. Cloud computing provides scalable computing resources over the Internet.
Cloud computing is a general term for networked services and resources provided over the internet. It allows users to access computing power, databases, and applications remotely through web services. Key characteristics include on-demand access to computing resources, elasticity to scale up or down based on needs, and a pay-as-you-go model where users only pay for what they use. Common cloud service models include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Virtualization is a core technology enabling cloud computing by allowing multiple virtual machines to run on a single physical machine. Major cloud providers include Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
- Problems with traditional data centers.
- Cloud computing definition, deployment, and services models.
- Essential characteristics of cloud services.
- IaaS examples.
- PaaS examples.
- SaaS examples.
- Cloud enabling technologies such as grid computing, utility computing, service oriented architecture (SOA), The Internet, Multi-tenancy, Web 2.0, Automation and Virtualization.
Cloud computing provides economic benefits through common infrastructure, location independence, online connectivity, utility pricing, and on-demand resources. Pooled, standardized resources lower overhead costs and increase utilization through statistical multiplexing. Aggregating independent workloads reduces variability, lowering the cost per delivered resource. In reality, workloads may be correlated, limiting these statistical economies. However, mid-size providers can achieve scale benefits by aggregating independent demands. Large cloud providers utilize scale through low-cost components and automation.
The success of application deployment on cloud depends a lot on the architecture style which in turn depends on your business needs. This presentation talks about the commonly used Architecture and business use cases.
Grid computing is the sharing of computer resources from multiple administrative domains to achieve common goals. It allows for independent, inexpensive access to high-end computational capabilities. Grid computing federates resources like computers, data, software and other devices. It provides a single login for users to access distributed resources for tasks like drug discovery, climate modeling and other data-intensive applications. Current grids are used for distributed supercomputing, high-throughput computing, on-demand computing and other methods. Grids benefit scientists, engineers and other users who need to solve large problems or collaborate globally.
This document discusses cloud computing, including:
1. It defines cloud computing as internet-based computing where virtual servers provide resources like software, infrastructure, platforms and devices to customers on a pay-as-you-use basis.
2. It describes the main types of clouds: SaaS, PaaS, and IaaS which provide software, platforms, and infrastructure as services respectively.
3. It outlines some key advantages like pay-as-you-use, location independence, instant scalability, and abstraction which allows enterprises to focus on their core business.
Green computing refers to using computing resources efficiently and minimizing environmental impact. It involves implementing energy-efficient policies and practices when setting up and operating IT systems. The goals of green computing include minimizing energy consumption, purchasing green energy, and reducing employee/customer travel requirements. Green cloud computing aims to achieve efficient infrastructure utilization and processing while minimizing energy usage. It uses techniques like dynamic resource allocation and powering down underutilized servers.
Load Balancing In Cloud Computing:A ReviewIOSR Journals
Abstract: As the IT industry is growing day by day, the need of computing and storage is increasing
rapidly. The amount of data exchanged over the network is constantly increasing. Thus the process of this
increasing mass of data requires more computer equipment to meet the various needs of the organizations.
To better capitalize their investment, the over-equipped organizations open their infrastructures to others by
exploiting the Internet and other important technologies such as virtualization by creating a new computing
model: the cloud computing. Cloud computing is one of the significant milestones in recent times in the
history of computers. The basic concept of cloud computing is to provide a platform for sharing of resources
which includes software and infrastructure with the help of virtualization. This paper presents a brief review
of cloud computing. The main emphasize of this paper is on the load balancing technique in cloud
computing.
Keywords: Cloud Computing, Load Balancing, Dynamic Load Balancing, Virtualization, Data Center.
Infrastructure as a Service ( IaaS) is one of the three fundamental services in cloud computing. IaaS provides access to basic computing resources such as hardware- processor, storage , network cards and more
The document discusses enabling technologies for distributed and cloud computing over the past 30 years. It describes how computing has evolved from centralized mainframes and supercomputers to today's distributed systems using grids, peer-to-peer networks, and internet clouds. It also discusses the interactions between challenges like data deluge, cloud technologies, e-science, and parallel computing.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services that can be provisioned with minimal management effort. It has characteristics like on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. The cloud services models are Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS). The deployment models are private cloud, community cloud, public cloud and hybrid cloud.
A quick overview of the possible business models of the cloud computing companies. Done for Tampere University of Technology seminar course about cloud computing ( http://www.cs.tut.fi/~tsysta/Pilvilaskenta.html ).
The document discusses cloud resource management and cloud computing architecture. It covers the following key points in 3 sentences:
Cloud architecture can be broadly divided into the front end, which consists of interfaces and applications for accessing cloud platforms, and the back end, which comprises resources for providing cloud services like storage, virtual machines, and security mechanisms. Common cloud service models include infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Virtualization techniques allow for the sharing of physical resources among multiple organizations by assigning logical names to physical resources and providing pointers to access them.
Cloud computing allows users to access virtual hardware, software, platforms, and services on an as-needed basis without large upfront costs or commitments. This transforms computing into a utility that can be easily provisioned and composed. The long-term vision is for an open global marketplace where IT services are freely traded like utilities, lowering barriers and allowing flexible access to resources and software for all users.
cloud computing, Principle and Paradigms: 1 introdutionMajid Hajibaba
The document is a presentation on cloud computing that covers its principles, paradigms, and various models. It defines cloud computing, discusses its roots in technologies like grid computing and virtualization, and describes the different layers including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It also covers deployment models, desired features, infrastructure management challenges, and examples of cloud providers like Amazon Web Services.
The document discusses cloud computing, providing definitions and an overview of key concepts. It describes the three main cloud service models - Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Examples of applications are given for each model. Advantages of cloud computing include lower costs, automatic software updates, unlimited storage, and collaboration capabilities. However, cloud computing also has disadvantages such as reliance on internet connectivity and potential security and data loss issues.
Introduction to Cloud Computing and Cloud InfrastructureSANTHOSHKUMARKL1
Introduction, Cloud Infrastructure: Cloud computing, Cloud computing delivery models and services, Ethical issues, Cloud vulnerabilities, Cloud computing at Amazon, Cloud computing the Google perspective, Microsoft Windows Azure and online services, Open-source software platforms for private clouds.
A brief discussion about Cloud computing for a beginner, you can get a clear idea about cloud computing from this slides.Also, discuss cloudsim simulator.
Cloud computing & energy efficiency using cloud to decrease the energy use in...Puru Agrawal
Cloud can be used to decrease the energy use in large companies. This presentation deals with a model which explains as how cloud can be used to decrease the energy uses. This is a field related to green computing and minimum use of energy resources.
The document discusses several security challenges related to cloud computing. It covers topics like data breaches, misconfiguration issues, lack of cloud security strategy, insufficient identity and access management, account hijacking, insider threats, and insecure application programming interfaces. The document emphasizes that securing customer data and applications is critical for cloud service providers to maintain trust and meet compliance requirements.
This document provides an overview of different distributed computing models including cluster computing, grid computing, peer-to-peer networks, and cloud computing. It describes key characteristics of each model such as architecture, advantages, disadvantages, and applications. Cluster computing uses interconnected stand-alone computers that work cooperatively, while grid computing consists of distributed systems from different administrative domains. Peer-to-peer networks allow sharing of files directly between nodes without a centralized server. Cloud computing provides scalable computing resources over the Internet.
Cloud computing is a general term for networked services and resources provided over the internet. It allows users to access computing power, databases, and applications remotely through web services. Key characteristics include on-demand access to computing resources, elasticity to scale up or down based on needs, and a pay-as-you-go model where users only pay for what they use. Common cloud service models include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Virtualization is a core technology enabling cloud computing by allowing multiple virtual machines to run on a single physical machine. Major cloud providers include Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
- Problems with traditional data centers.
- Cloud computing definition, deployment, and services models.
- Essential characteristics of cloud services.
- IaaS examples.
- PaaS examples.
- SaaS examples.
- Cloud enabling technologies such as grid computing, utility computing, service oriented architecture (SOA), The Internet, Multi-tenancy, Web 2.0, Automation and Virtualization.
Cloud computing provides economic benefits through common infrastructure, location independence, online connectivity, utility pricing, and on-demand resources. Pooled, standardized resources lower overhead costs and increase utilization through statistical multiplexing. Aggregating independent workloads reduces variability, lowering the cost per delivered resource. In reality, workloads may be correlated, limiting these statistical economies. However, mid-size providers can achieve scale benefits by aggregating independent demands. Large cloud providers utilize scale through low-cost components and automation.
The success of application deployment on cloud depends a lot on the architecture style which in turn depends on your business needs. This presentation talks about the commonly used Architecture and business use cases.
Grid computing is the sharing of computer resources from multiple administrative domains to achieve common goals. It allows for independent, inexpensive access to high-end computational capabilities. Grid computing federates resources like computers, data, software and other devices. It provides a single login for users to access distributed resources for tasks like drug discovery, climate modeling and other data-intensive applications. Current grids are used for distributed supercomputing, high-throughput computing, on-demand computing and other methods. Grids benefit scientists, engineers and other users who need to solve large problems or collaborate globally.
This document discusses cloud computing, including:
1. It defines cloud computing as internet-based computing where virtual servers provide resources like software, infrastructure, platforms and devices to customers on a pay-as-you-use basis.
2. It describes the main types of clouds: SaaS, PaaS, and IaaS which provide software, platforms, and infrastructure as services respectively.
3. It outlines some key advantages like pay-as-you-use, location independence, instant scalability, and abstraction which allows enterprises to focus on their core business.
Green computing refers to using computing resources efficiently and minimizing environmental impact. It involves implementing energy-efficient policies and practices when setting up and operating IT systems. The goals of green computing include minimizing energy consumption, purchasing green energy, and reducing employee/customer travel requirements. Green cloud computing aims to achieve efficient infrastructure utilization and processing while minimizing energy usage. It uses techniques like dynamic resource allocation and powering down underutilized servers.
Load Balancing In Cloud Computing:A ReviewIOSR Journals
Abstract: As the IT industry is growing day by day, the need of computing and storage is increasing
rapidly. The amount of data exchanged over the network is constantly increasing. Thus the process of this
increasing mass of data requires more computer equipment to meet the various needs of the organizations.
To better capitalize their investment, the over-equipped organizations open their infrastructures to others by
exploiting the Internet and other important technologies such as virtualization by creating a new computing
model: the cloud computing. Cloud computing is one of the significant milestones in recent times in the
history of computers. The basic concept of cloud computing is to provide a platform for sharing of resources
which includes software and infrastructure with the help of virtualization. This paper presents a brief review
of cloud computing. The main emphasize of this paper is on the load balancing technique in cloud
computing.
Keywords: Cloud Computing, Load Balancing, Dynamic Load Balancing, Virtualization, Data Center.
Infrastructure as a Service ( IaaS) is one of the three fundamental services in cloud computing. IaaS provides access to basic computing resources such as hardware- processor, storage , network cards and more
The document discusses enabling technologies for distributed and cloud computing over the past 30 years. It describes how computing has evolved from centralized mainframes and supercomputers to today's distributed systems using grids, peer-to-peer networks, and internet clouds. It also discusses the interactions between challenges like data deluge, cloud technologies, e-science, and parallel computing.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services that can be provisioned with minimal management effort. It has characteristics like on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. The cloud services models are Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS). The deployment models are private cloud, community cloud, public cloud and hybrid cloud.
The document discusses cloud computing and provides an overview of related topics:
- It defines computing and lists trends in computing such as distributed computing, grid computing, cluster computing, and utility computing that led to cloud computing.
- It describes cloud computing architecture including service models (IaaS, PaaS, SaaS), deployment models, and management of services, resources, data, security, and research trends in cloud computing.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications and services. It has essential characteristics like on-demand self-service, broad network access, resource pooling and rapid elasticity. The cloud services models include Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). The deployment models are private cloud, community cloud, public cloud and hybrid cloud.
The document provides an overview of the evolution of cloud computing from its roots in mainframe computing, distributed systems, grid computing, and cluster computing. It discusses how hardware virtualization, Internet technologies, distributed computing concepts, and systems management techniques enabled the development of cloud computing. The document then describes several early technologies and models such as time-shared mainframes, distributed systems, grid computing, and cluster computing that influenced the development of cloud computing.
Datacenter and cloud architectures continue to evolve to address the needs of large-scale multi-tenant data centers and clouds. These needs are centered around dimensions such as scalability in computing, storage, and bandwidth, scalability in network services, efficiency in resource utilization, agility in service creation, cost efficiency, service reliability, and security. Data centers are interconnected across the wide area network via routing and transport technologies to provide a pool of resources, known as the cloud. High-speed optical interfaces and dense wavelength-division multiplexing optical transport are used to provide for high-capacity transport intra- and inter-datacenter. This presentation will provide some brief descriptions on the working principles of Cloud & Data Center Networks.
The document provides details about a cloud computing course being taught by Mr. Saurabh Gupta. It begins with an introduction to cloud computing and the traditional approach of running IT applications. It then discusses key concepts like distributed computing, client-server computing, parallel computing, and utility computing that led to the development of cloud computing. The rest of the document discusses cloud characteristics, service providers, advantages, and differences between concepts like elasticity vs scalability.
This document provides an overview of cloud computing, including its history and origins dating back to mainframe computers in the 1950s and time sharing networks in the 1960s. It describes the types of cloud models including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). The key characteristics of cloud computing are also summarized such as resource pooling, broad network access, elasticity, measured service, and on-demand self-service.
Cloud computing provides on-demand access to shared computing resources like networks, servers, storage, applications, and services. It has characteristics like on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. The document discusses various cloud service models like SaaS, PaaS, and IaaS and deployment models like private, community, and public clouds. It also covers distributed, grid, cluster, and utility computing concepts related to cloud.
Introduction to Cloud Computing
Cloud computing is a transformative technology that allows businesses and individuals to access computing resources over the internet. Instead of owning and maintaining physical hardware and software, users can leverage cloud services provided by companies like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and others. This shift has revolutionized how we think about IT infrastructure, software development, data storage, and more.
Key Concepts of Cloud Computing
On-Demand Self-Service:
Users can provision computing resources as needed without human intervention from the service provider. This includes servers, storage, and applications.
Broad Network Access:
Cloud services are available over the network and accessed through standard mechanisms, enabling use from a variety of devices like laptops, smartphones, and tablets.
Resource Pooling:
Providers use a multi-tenant model to serve multiple customers with dynamically assigned resources. This model allows for economies of scale and efficient resource utilization.
Rapid Elasticity:
Resources can be elastically provisioned and released, sometimes automatically, to scale rapidly outward and inward commensurate with demand.
Measured Service:
Cloud systems automatically control and optimize resource use by leveraging a metering capability, allowing for pay-as-you-go pricing models.
Types of Cloud Computing Services
Infrastructure as a Service (IaaS):
Provides virtualized computing resources over the internet. Examples include AWS EC2, Google Compute Engine, and Azure Virtual Machines.
Platform as a Service (PaaS):
Offers hardware and software tools over the internet, typically used for application development. Examples include Google App Engine, AWS Elastic Beanstalk, and Azure App Services.
Software as a Service (SaaS):
Delivers software applications over the internet, on a subscription basis. Examples include Google Workspace, Microsoft Office 365, and Salesforce.
Deployment Models
Public Cloud:
Services are delivered over the public internet and shared across multiple organizations. It offers cost savings but might pose concerns regarding data security and privacy.
Private Cloud:
Dedicated to a single organization, offering enhanced security and control over data and infrastructure. It's more expensive than public cloud but can be tailored to specific business needs.
Hybrid Cloud:
Combines public and private clouds, allowing data and applications to be shared between them. This model offers greater flexibility and optimization of existing infrastructure, security, and compliance.
Community Cloud:
Shared between organizations with common concerns (e.g., security, compliance, jurisdiction). It can be managed internally or by a third-party.
Advantages of Cloud Computing
Cost Efficiency: Reduces the need for significant capital expenditure on hardware and software.
Scalability and Flexibility: Easily scales up or down based on
This document outlines the course outcomes and topics to be covered for a Cloud Computing elective course. The course aims to describe system models, analyze virtualization mechanisms, demonstrate cloud architectural design and security, and construct cloud-based software applications. The topics covered in Unit 1 include scalable computing over the internet, technologies for network-based systems, system models for distributed and cloud computing, software environments, and performance, security and energy efficiency. Specific topics in Unit 1 range from multicore CPUs and virtualization to models like clusters, grids, peer-to-peer networks and cloud computing.
introduction to cloud computing for college.pdfsnehan789
The document provides an overview of cloud computing by outlining its module which includes fundamental concepts of distributed systems, cluster computing, grid computing, cloud computing, and mobile computing. It then defines computing and distributed systems, explaining that a distributed system is a system with multiple components located on different machines that communicate and coordinate actions to appear as a single system. Key characteristics of distributed systems include presenting a single system image, expandability, continuous availability, and being supported by middleware.
This document provides an overview of cloud computing and related topics such as distributed systems, cluster computing, and mobile computing. It defines cloud computing as a technology that allows for network-based computing over the Internet, providing hardware, software, and networking services to clients. Key aspects include on-demand services that are scalable and available anywhere via simple interfaces. The document contrasts cloud computing with cluster computing, noting that clusters have tightly coupled nodes within a local network, while clouds have loosely coupled nodes that can span wide geographic areas. Examples of cloud computing applications in areas like healthcare, engineering, education, and media are also provided.
e-Infrastructure available for research, using the right tool for the right jobDavid Wallom
This document provides an overview of e-infrastructure resources available for research. It describes what e-infrastructure is and its main components like data storage, software, hardware, networks, security, and people. It discusses different types of computational resources including supercomputers, parallel programming, high performance computing, distributed and shared memory models, and GPU computing. It also outlines institutional, regional, national, and international e-infrastructure resources in the UK like advanced computing centers, EPSRC regional centers, HECToR/ARCHER, and PRACE. Finally, it briefly discusses high throughput computing and examples of applications of e-infrastructure like virus analysis, fusion reactor modeling, and Alzheimer's disease research.
The document discusses various elements of systems design. It describes components that require design such as the network, application architecture, user interfaces, and system interfaces. It also discusses inputs to the design process such as functional models from analysis. The document then covers specific design areas in more detail, including network design, the application architecture using various models like client-server and n-tier architectures, user interface design, and database design. It also discusses design techniques like prototyping.
1. Grid computing is a distributed computing approach that allows users to access computational resources over a network. It aims to dynamically allocate resources like processing power, storage, or software according to user demands.
2. Grid computing provides a utility-like model for accessing computing resources. Users can access resources from a grid in the same way users access utilities like power or water grids.
3. Key benefits of grid computing include maximizing resource utilization, providing fast and cheap computing services, and enabling collaboration through secure resource sharing across organizations. Grid computing has applications in scientific research, businesses, and e-governance.
Cloud computing comes into focus only when you think about what IT always needs: a way to increase capacity or add capabilities on the fly without investing in new infrastructure, training new personnel, or licensing new software. Cloud computing encompasses any subscription-based or pay-per-use service that, in real time over the Internet, extends IT's existing capabilities.
This document provides an overview of cluster computing. It defines a cluster as a group of loosely coupled computers that work together closely to function as a single computer. Clusters improve speed and reliability over a single computer and are more cost-effective. Each node has its own operating system, memory, and sometimes file system. Programs use message passing to transfer data and execution between nodes. Clusters can provide low-cost parallel processing for applications that can be distributed. The document discusses cluster architecture, components, applications, and compares clusters to grids and cloud computing.
INTRODUCTION TO BIG DATA AND HADOOP
9
Introduction to Big Data, Types of Digital Data, Challenges of conventional systems - Web data, Evolution of analytic processes and tools, Analysis Vs reporting - Big Data Analytics, Introduction to Hadoop - Distributed Computing
Challenges - History of Hadoop, Hadoop Eco System - Use case of Hadoop – Hadoop Distributors – HDFS – Processing Data with Hadoop – Map Reduce.
The document discusses cloud computing architectures and services. It describes layered cloud architecture design, including public, private and hybrid clouds. It explains Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). IaaS provides computing infrastructure on-demand. PaaS provides platforms for developers to build applications. SaaS provides software to users on a subscription basis.
This document discusses intellectual property rights (IPR) in academic research. It begins by outlining current technology trends such as artificial intelligence, machine learning, blockchain, and more. It then discusses how academic researchers can find information on current research trends through sources like patents and collaborating with industry. The document provides an example of the top five patent filing companies in 2019, including IBM, Samsung, Canon, Microsoft, and Intel. Finally, it outlines the patent process and how researchers can utilize patents to inform their work and identify problems and solutions.
To file a patent in India, there are several rules and fees that must be followed. The key steps include determining the patentability of the invention, conducting a patent search, drafting the patent application which can be done yourself or with the assistance of a law firm or facilitator for a fee, submitting the application and paying the minimum fees of Rs. 8,900, receiving a first examination report within 48 months, drafting a reply with the assistance of a law firm or facilitator, and attending a potential hearing. If the hearing is successful, the patent will be granted, with the normal procedure taking 4-5 years total.
This document provides an overview of algorithms and algorithm analysis. It discusses key concepts like what an algorithm is, different types of algorithms, and the algorithm design and analysis process. Some important problem types covered include sorting, searching, string processing, graph problems, combinatorial problems, geometric problems, and numerical problems. Examples of specific algorithms are given for some of these problem types, like various sorting algorithms, search algorithms, graph traversal algorithms, and algorithms for solving the closest pair and convex hull problems.
1. Machine learning is a set of techniques that use data to build models that can make predictions without being explicitly programmed.
2. There are two main types of machine learning: supervised learning, where the model is trained on labeled examples, and unsupervised learning, where the model finds patterns in unlabeled data.
3. Common machine learning algorithms include linear regression, logistic regression, decision trees, support vector machines, naive Bayes, k-nearest neighbors, k-means clustering, and random forests. These can be used for regression, classification, clustering, and dimensionality reduction.
Resource management techniques involve efficiently using an organization's limited resources such as employees, equipment, and finances. Some key techniques include:
1. Linear programming, which uses mathematical models to determine the optimal allocation of resources to meet objectives and constraints. An example is determining the optimal product mix.
2. Operations research, which applies scientific principles and quantitative analysis to help maximize efficiency. It has been widely used by militaries and businesses since World War II.
3. Modeling real-world problems mathematically and using algorithms to determine the best solutions while optimizing objectives under constraints. This allows organizations to best utilize their resources.
Ge6075 professional ethics in engineering unit 1Dr Geetha Mohan
Morals, values and Ethics – Integrity – Work ethic – Service learning – Civic virtue – Respect for others – Living peacefully – Caring – Sharing – Honesty – Courage – Valuing time – Cooperation – Commitment – Empathy – Self confidence – Character – Spirituality – Introduction to Yoga and meditation for professional excellence and stress management.
Cp7101 design and management of computer networks-flow analysisDr Geetha Mohan
The document discusses network traffic flows, including defining flows as sets of traffic with common attributes. It describes different types of flows like individual and composite flows. It also covers flow characteristics, identifying flows based on applications and devices, and developing flow models and specifications. Flows can be analyzed and prioritized based on performance needs and other attributes to help design and manage computer networks.
Cp7101 design and management of computer networks-requirements analysis 2 Dr Geetha Mohan
This document discusses the requirements analysis process for designing and managing computer networks. It involves gathering requirements through determining initial conditions, setting customer expectations, working with users, taking performance measurements, and tracking requirements. Key aspects of requirements analysis include developing service metrics, characterizing user and application behavior, and establishing performance requirements for delay, capacity, and other metrics. The overall goal is to understand network usage and specify requirements to guide the network design.
Cp7101 design and management of computer networks-requirements analysisDr Geetha Mohan
The document discusses requirements analysis for computer networks. It defines requirements analysis as gathering and deriving requirements to understand system and network behaviors. This includes identifying, gathering, and understanding system requirements and their characteristics. Requirements can be core/fundamental requirements necessary for network success or features that are desired but not necessary. Requirements analysis results in a requirements specification and map to guide network architecture and design. The document outlines different types of requirements including user, application, device, network, and other requirements.
Cp7101 design and management of computer networks-design conceptsDr Geetha Mohan
This document discusses network design concepts and products. It describes three orders of network design products - first, second, and third-order - which provide increasing levels of detail about network devices, locations, configurations and connectivity. Key network design products include network blueprints, a component plan, vendor selections, traceability, and metrics. The design process involves evaluating vendors and laying out the network topology. Architecture products document design decisions while analysis products identify requirements and problems.
Cp7101 design and management of computer networks -networkDr Geetha Mohan
This document discusses network analysis, architecture, and design. It covers:
1) The importance of network analysis in defining problems and requirements before establishing network architecture and design.
2) How network architecture uses the information from analysis to develop a high-level structure and make technology and topology choices.
3) How network design provides physical detail to the architecture by selecting locations, equipment, and vendors.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
1. IT19741
Cloud and Big Data
Analytics
Dr G Geetha
Dean innovation and Professor CSE
Women Scientist, Qualified Patent agent
2. UNIT-I CLOUD
ENABLING
TECHNOLOGIES
Technologies for Network-Based Systems -
System Models for Distributed and Cloud
Computing - Implementation Levels of
Virtualization - Virtualization Structures/Tools
and Mechanisms - Virtualization of CPU,
Memory, and I/O Devices - Virtual Clusters
and Resource Management - Virtualization for
Data-Center Automation.
3. 1.1 Technologies for Network-Based Systems
1. Multicore CPUs and Multithreading Technologies
2. GPU Computing to Exascale and Beyond
3. Memory, Storage, and Wide-Area Networking
4. Virtual Machines and Virtualization Middleware
5. Data Center Virtualization for Cloud Computing
5. 5
From Desktop/HPC/Grids to Internet Clouds
in 30 Years
• HPC moving from centralized supercomputers to geographically distributed
desktops, desksides, clusters, and grids to clouds over last 30 years
• R/D efforts on HPC, clusters, Grids, P2P, and virtual machines has laid the
foundation of cloud computing that has been greatly advocated since 2007
• Location of computing infrastructure in areas with lower costs in hardware,
software, datasets, space, and power requirements – moving from desktop
computing to datacenter-based clouds
8. 8
Computing Paradigm Distinctions
• Centralized Computing
• All computer resources are centralized in one physical system.
• Parallel Computing
• All processors are either tightly coupled with central shard memory or loosely coupled with
distributed memory
• Distributed Computing
• Field of CS/CE that studies distributed systems. A distributed system consists of multiple
autonomous computers, each with its own private memory, communicating over a network.
• Cloud Computing
• An Internet cloud of resources that may be either centralized or decentralized. The cloud
apples to parallel or distributed computing or both. Clouds may be built from physical or
virtualized resources.
14. 14
Multi-threading Processors
• Four-issue superscalar (e.g. Sun Ultrasparc I)
• Implements instruction level parallelism (ILP) within a single processor.
• Executes more than one instruction during a clock cycle by sending multiple
instructions to redundant functional units.
• Fine-grain multithreaded processor
• Switch threads after each cycle
• Interleave instruction execution
• If one thread stalls, others are executed
• Coarse-grain multithreaded processor
• Executes a single thread until it reaches certain situations
• Simultaneous multithread processor (SMT)
• Instructions from more than one thread can execute in any given pipeline stage
at a time.
15. 15
5 Micro-architectures of CPUs
Each row represents the issue slots for a single execution cycle:
• A filled box indicates that the processor found an instruction to execute in that
issue slot on that cycle;
• An empty box denotes an unused slot.
19. 19
GPU Performance
Bottom – CPU - 0.8 Gflops/W/Core (2011)
Middle – GPU - 5 Gflops/W/Core (2011)
Top - EF – Exascale computing (10^18 Flops)
20. 20
Interconnection Networks
• SAN (storage area network) - connects servers with disk arrays
• LAN (local area network) – connects clients, hosts, and servers
• NAS (network attached storage) – connects clients with large storage
systems
22. 22
Virtual Machines
• Eliminate real machine constraint
• Increases portability and flexibility
• Virtual machine adds software to a physical machine to give it the
appearance of a different platform or multiple platforms.
• Benefits
• Cross platform compatibility
• Increase Security
• Enhance Performance
• Simplify software migration
23. 23
Initial Hardware Model
All applications access hardware resources (i.e. memory, i/o)
through system calls to operating system (privileged
instructions)
Advantages
Design is decoupled (i.e. OS people can develop OS
separate of Hardware people developing hardware)
Hardware and software can be upgraded without notifying
the Application programs
Disadvantage
Application compiled on one ISA will not run on another
ISA.
Applications compiled for Mac use different operating
system calls then application designed for windows.
ISA’s must support old software
Can often be inhibiting in terms of performance
Since software is developed separately from hardware…
Software is not necessarily optimized for hardware.
24. 24
Virtual Machine Basics
• Virtual software placed between underlying
machine and conventional software
• Conventional software sees different ISA from the
one supported by the hardware
• Virtualization process involves:
• Mapping of virtual resources (registers and
memory) to real hardware resources
• Using real machine instructions to carry out the
actions specified by the virtual machine
instructions
26. 1.2 System Models for Distributed and Cloud
Computing
1. Clusters of Cooperative Computers
2. Grid Computing Infrastructures
3. Peer-to-Peer Network Families
4. Cloud Computing over the Internet .
31. 31
Peer-to-Peer (P2P) Network
• A distributed system architecture
• Each computer in the network can act as a client or server for other netwpork
computers.
• No centralized control
• Typically many nodes, but unreliable and heterogeneous
• Nodes are symmetric in function
• Take advantage of distributed, shared resources (bandwidth, CPU, storage) on
peer-nodes Fault-tolerant, self-organizing Operate in dynamic environment,
frequent join and leave is the norm
32. 32
Peer-to-Peer (P2P) Network
Overlay network - computer network built on top of another network.
• Nodes in the overlay can be thought of as being connected by virtual or logical links, each of which
corresponds to a path, perhaps through many physical links, in the underlying network.
• For example, distributed systems such as cloud computing, peer-to-peer networks, and client-server
applications are overlay networks because their nodes run on top of the Internet.
37. 37
Cloud Service Models (1)
Infrastructure as a service (IaaS)
• Most basic cloud service model
• Cloud providers offer computers, as physical or more often as virtual machines,
and other resources.
• Virtual machines are run as guests by a hypervisor, such as Xen or KVM.
• Cloud users deploy their applications by then installing operating system images
on the machines as well as their application software.
• Cloud providers typically bill IaaS services on a utility computing basis, that is,
cost will reflect the amount of resources allocated and consumed.
• Examples of IaaS include: Amazon Cloud Formation (and underlying services
such as Amazon EC2), Rackspace Cloud, Terre mark, and Google Compute
Engine.
38. 38
Cloud Service Models (2)
Platform as a service (PaaS)
• Cloud providers deliver a computing platform typically including operating system,
programming language execution environment, database, and web server.
• Application developers develop and run their software on a cloud platform without
the cost and complexity of buying and managing the underlying hardware and
software layers.
• Examples of PaaS include: Amazon Elastic Beanstalk, Cloud Foundry, Heroku,
Force.com, EngineYard, Mendix, Google App Engine, Microsoft Azure and
OrangeScape.
39. 39
Cloud Service Models (3)
Software as a service (SaaS)
• Cloud providers install and operate application software in the cloud and cloud
users access the software from cloud clients.
• The pricing model for SaaS applications is typically a monthly or yearly flat fee
per user, so price is scalable and adjustable if users are added or removed at
any point.
• Examples of SaaS include: Google Apps, innkeypos, Quickbooks Online,
Limelight Video Platform, Salesforce.com, and Microsoft Office 365.
40. 40
Service-oriented architecture (SOA)
• SOA is an evolution of distributed computing based on the request/reply design
paradigm for synchronous and asynchronous applications.
• An application's business logic or individual functions are modularized and
presented as services for consumer/client applications.
• Key to these services - their loosely coupled nature;
• i.e., the service interface is independent of the implementation.
• Application developers or system integrators can build applications by composing
one or more services without knowing the services' underlying implementations.
• For example, a service can be implemented either in .Net or J2EE, and the
application consuming the service can be on a different platform or language.
41. 41
SOA key characteristics:
• SOA services have self-describing interfaces in platform-independent XML documents.
• Web Services Description Language (WSDL) is the standard used to describe the services.
• SOA services communicate with messages formally defined via XML Schema (also called
XSD).
• Communication among consumers and providers or services typically happens in
heterogeneous environments, with little or no knowledge about the provider.
• Messages between services can be viewed as key business documents processed in an
enterprise.
• SOA services are maintained in the enterprise by a registry that acts as a directory listing.
• Applications can look up the services in the registry and invoke the service.
• Universal Description, Definition, and Integration (UDDI) is the standard used for service
registry.
• Each SOA service has a quality of service (QoS) associated with it.
• Some of the key QoS elements are security requirements, such as authentication and
authorization, reliable messaging, and policies regarding who can invoke services.
47. 1.3 Implementation Levels of Virtualization
1. Levels of Virtualization Implementation
2. VMM Design Requirements and Providers
3. Virtualization Support at the OS Level
4. Middleware Support for Virtualization
64. 1.4 Virtualization Structures/Tools and
Mechanisms
• Hypervisor and Xen Architecture
• Binary Translation with Full Virtualization
• Para-Virtualization with Compiler Support
78. 1.5 Virtualization of CPU, Memory, and I/O
Devices
• Hardware Support for Virtualization
• CPU Virtualization
• Memory Virtualization
• I/O Virtualization
• Virtualization in Multi-Core Processors
82. 1.6 Virtual Clusters and Resource
Management
• Physical versus Virtual Clusters
• Live VM Migration Steps and Performance Effects
• Migration of Memory, Files, and Network Resources
• Dynamic Deployment of Virtual Clusters
98. 1.7 Virtualization for Data-Center Automation
• Server Consolidation in Data Centers
Server consolidation is the process of migrating network services and applications
from multiple computers to a singular computer. This consolidation can include
multiple physical computers to multiple virtual computers on one host computer
• Virtual Storage Management
Virtual Storage Management provides end-to-end view of the storage assigned to
client logical partition.
• Cloud OS for Virtualized Data Centers
vSphere is primarily intended to offer virtualization support and resource
management of data-center resources in building private clouds.
• Trust Management in Virtualized Data Centers
assures secure data access through trustworthy cloud service provider
105. 1.1 Technologies for Network-Based Systems
1. Multicore CPUs and Multithreading Technologies
2. GPU Computing to Exascale and Beyond
3. Memory, Storage, and Wide-Area Networking
4. Virtual Machines and Virtualization Middleware
5. Data Center Virtualization for Cloud Computing
106. 1.2 System Models for Distributed and Cloud
Computing
1. Clusters of Cooperative Computers
2. Grid Computing Infrastructures
3. Peer-to-Peer Network Families
4. Cloud Computing over the Internet .
107. 1.3 Implementation Levels of Virtualization
1. Levels of Virtualization Implementation
2. VMM Design Requirements and Providers
3. Virtualization Support at the OS Level
4. Middleware Support for Virtualization
108. 1.4 Virtualization Structures/Tools and
Mechanisms
• Hypervisor and Xen Architecture
• Binary Translation with Full Virtualization
• Para-Virtualization with Compiler Support
109. 1.5 Virtualization of CPU, Memory, and I/O
Devices
• Hardware Support for Virtualization
• CPU Virtualization
• Memory Virtualization
• I/O Virtualization
• Virtualization in Multi-Core Processors
110. 1.6 Virtual Clusters and Resource
Management
• Physical versus Virtual Clusters
• Live VM Migration Steps and Performance Effects
• Migration of Memory, Files, and Network Resources
• Dynamic Deployment of Virtual Clusters
111. 1.7 Virtualization for Data-Center Automation
• Server Consolidation in Data Centers
• Virtual Storage Management
• Cloud OS for Virtualized Data Centers
• Trust Management in Virtualized Data Centers