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Cloud computing can be defined as a service that provide the facility to store data on internet instead of local server or a personal computer and also provides resources through web based tools. It is the study of business aspects of cloud computation, Amazon cloud computation, windows azure, Google app engines and various security and privacies in cloud computation.It focuses on Tracking, Resource allocation, Heterogeneous computing resources, security issues and Access to end users etc. It involves three components i.e. Client computers, Distributed server and Data centers.

Cloud Computing supports three types of models:

  • Software as a Service: It includes business intelligence, web conference, automation, web-based emails, office automation suites etc.
  • Platform as a Service: It helps to develop, manage and deploy the customer-acquired applications using programming languages, tools and services supported by the service providers
  • Infrastructure as a Service: It provides services such as storage, processing, network based and other computing resources where users can run software compiled with Operating Systems

Cloud Computing is based on various structures such as Hypervisor Clustering Architecture, Zero Downtime Architecture, Resource Reservation Architecture, Bare-Metal Architecture, Storage Management Architecture, Virtual Server Architecture, Rapid Provisioning Architecture, Mobile Cloud Computing, MobiByte and Crowd Computing.

Various Topics are covered by Cloud Computing are Infrastructure, Visualization of clouds, Cloud simulation, Security in cloud computation and Privacy, Parallel Computing and Distributed System, Big Data , PaaS, SaaS, IaaS

Client computers ,Distributed server and Data centers.

  • Client computers – Those users which interact with clouds are termed as clients. Mobile, thick, thin are the three types of clients.
  • Distributed server – server provide response to the data which are requested by the client. There are large number of servers in different places but they act as they are working next to each other.
  • Data centers - It is the collection of the server where data can be accessed through the internet.

Advantages of cloud computing: 

  • Network complexity is reduced.
  • Provides efficiency.
  • More reliable.
  • No loss of the stored information.
  • No need of software licenses.

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 is known as cloud computing. It is that type of internet-based computing which provides shared computer processing resources and data to computers and other devices on demand. 

Topics included to make your understanding better are given below:

  • Infrastructure, Visualization of clouds, Cloud simulation, Security in cloud computation and Privacy.

Cloud computation involves study of various other systems such as studying the business aspects of cloud computation, Amazon cloud computation, windows azure, Google app engines and various security and privacies in cloud computation.

It is possible to separate the processes related to building of infrastructure for services got from end user services all this is done with the help of cloud computation. It mainly works on the flexibility of any application that how much flexible is an application for the user to execute. It describes about software, computation, data accessed and storage services without the requirement of any end user knowledge of physical location and configuration of systems that is delivery of services. A parallel concept of electricity grid runs where the end users consume power resources without any prior understanding with the component devices.

Agility improves with the users or the understanding of any software or devices improves with the understanding of user. Application Programming Interface (API) determines the accessibility of software and enables the machines to interact with cloud software the way the user interface interaction takes place between computer and human. Big data is used to manage the backend and the cloud computing systems make use of REST-based API’s. Multi-tenancy enables costs across large pool of users and determines the sharing of resources.

 To improve the reliability of any system we make use of multiple redundant sites which are responsible for business continuity and recovery of data and find an ease in designing of cloud computation.

Cloud computing systems comprises of three major components:

  • Client Computers: It deals with interaction of users with clouds
  • Distributed Server: Response of data requested by the client is given by the server
  • Data Centers: Collection of servers where data can be accessed over the internet

Cloud integration: Process where data is shared in the cloud with configuration of multiple application programs. Network that incorporates cloud integration then at that time diverse applications communicate either directly or with the help of third-party software.

Features of cloud integration platform are:

  • Security, Reliability, Return of investment, Scalability, Integrity and Compatibility, Cloud Service Models are of three types: SaaS, PaaS, IaaS, Software as a Service (SaaS):  A highly advanced and complex cloud model. Service provider manages the software and allows the customers to use the applications running on cloud infrastructure and resolve their faults. The model includes business intelligence, web conference, automation, web-based emails, office automation suites etc. Platform as a Service (PaaS): Its main focus is on developing, managing, deploying the customer-acquired applications using programming languages, tools and services supported by the service providers. Customers have full control over the deployed applications and development tools but are unable to manage the cloud infrastructure.
  • Infrastructure as a Service (IaaS): This model deals with management control and user flexibility, it is the fundamental block for cloud IT. It provides us services such as storage, processing, network based and other computing resources where users can run software compiled with Operating Systems. Cloud Deployment models include private cloud, public cloud, community cloud and hybrid cloud, Private Cloud: It is used on personal needs here the cloud infrastructure is maintained for single organization. It’s operated either internally or by any third party and is hosted either internally or externally. It is used to improve the business environment.
  • Public Cloud: Services are open for public use but the services offered are slightly different than those in private cloud. Service providers like Amazon, Microsoft and Google manages the infrastructure at their center, Community Cloud: It is used for community purpose where infrastructure is shared between various organizations belonging to a particular community and is managed by a third party. Hybrid Cloud: It is a combination of private, public and community cloud which allows its services by integrating it with other cloud services and provide us early solutions. Cloud Management refers to the management of cloud computing products and services.

These systems must have the ability to perform certain tasks such as:

  • Tracking
  • Resource allocation
  • Heterogeneous computing resources should be managed
  • Monitoring the security issues
  • Access to end users

Some of the advanced cloud structures are:

  • Hypervisor Clustering Architecture
  • Zero Downtime Architecture
  • Resource Reservation Architecture
  • Bare-Metal Architecture
  • Storage Management Architecture
  • Virtual Server Architecture
  • Rapid Provisioning Architecture

Mobile Cloud Computing (MCC): It is a combination of mobile computing, cloud computing and wireless networks for making resources available to mobile users, network operators and cloud computation providers. Its main aim is to execute mobile applications on large amount of mobile devices.

MobiByte (framework): It’s a mobile cloud application development framework used to achieve energy efficiency, performance enhancement etc. Cloud Collaboration: It another way of sharing and co-authoring computer files by using the computing techniques. It’s a kind of collaboration which allows employees to work on documents and other data types. It is a platform used by the employees to share, edit and work together on projects.

Crowd Computing: It’s a merger of both cloud computing and crowd sourcing. It is a combination of human intelligence with artificial intelligence in order to produce a quality result at unmatched speed. Cloudlet: It’s a group of computers designed to provide computing services to devices like smart phones, tablets. It is specially designed to make our devices attractive and even support intensive and interactive mobile applications such as speech recognition, machine learning, language processing, virtual reality etc.

Various advanced topics included are given below:

  • Elasticity principles, Control algorithms, Analytics, Computing security, Hybrid cloud systems.
  • Cloud resource management, Semantic cloud, SOA, CAP Theorem, Data Virtualization.

Our Cloud Computing & Programming Assignment help tutors help with IDEs & multiple platforms for application development ,Cloud Architecture, Infrastructure as a Service, Cloud Strategic Impact,Cloud Risk Impact, Financial Impact,Requirements, Cloud computing means change in the delivery of Information Technology to end users by introducing the ability to deliver infrastructure, platforms, and software via the network.technologies, models, benefits and risks of cloud computing ,virtualization as one of the key building blocks of most cloud computing solutions.cloud computing, problems solved by cloud computing, benefits of deploying cloud technologies in an organisation.  

Some of the homework help topics include:

  • Cloud Platform as a Service,Cloud Software as a Service,cloud programming and software environments.
  • Cloud Benefits and Challenges,ubiquitous computing with clouds and the Internet of things.
  • App Engine, Amazon AWS, Microsoft Azure, and emerging cloud software stacks), resource management.

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Help for complex topics like:

  • Analysis,Draft Architecture,Cloud Computing Application Inventory,Service Components,User Profiles, Distributed system models and enabling technologies, computer clusters for scalable Computing, virtual machines and virtualization of clusters and datacenters, design of cloud computing platforms,  (Workflow Systems, MapReduce, Google  P2P computing with overlay networks,  and data-intensive distributed computing.
  • Google MapReduce / Yahoo Hadoop,Eucalyptus, Nimbus, OpenStack,Service-Oriented Architectures,Cloud Programming,Grid Computing,, End-to-end Design,Cloud Connectivity,Cloud Resilience,Cloud Security,Cloud Transition Management,Migration,Employee Changes,Service, Management,Administration,Cloud Monitoring,Support,Compliance,Risk,Governance,Cloud Systematic Refinement,Cloud Future Trends
  • Reference Architecture,Use Cases,Cloud Platform Definition,Google App Engine, Microsoft Windows Azure, Amazon Web,Services, and Other Platform Options,Browser Interface,Native Clients,Presentation Optimization,Real-Time Web, Authentication,Personalization,Cloud Computing Network and Application Integration,Storage,Cloud Computing Relational and Non-Relational Data,Reliability and Elasticity,Marketing,Payments,Cloud Computing Development, Testing, and Staging,Production,Configuration,Cloud Administration and Troubleshooting,Refinement
  • Set up Hadoop in a cluster and write data analytic programs, design patterns & practices of programming, MapReduce, Use Hadoop for a variety of data analysis tasks,cloud components fit together
  • Distributed Systems,SQL Databases,MapReduce.
  • Setting up SSH for a Hadoop cluster,Web Based Cluster UI,Components of Hadoop,The HDFS,patent data set,Adapting for Hadoops API changes,Streaming in Hadoop,Improving Performance with Combiners,Advanced MapReduce,Joining data from different sources Creating a Bloom Filter, Monitoring and Debugging on a production cluster,Tuning for performance,Cookbook,Passing Job Specific parameters to your tasks,Probing for Task Specific information,Partitioning into multiple Output files,Inputting from and Outputting to a database,Keeping Output in sorted order.
  • Setting permissions,Managing quotas,Removing DataNodes,Adding DataNodes,Managing NameNodes,Recovering from a failed NameNode,Designing Network Layout and rack awareness,Scheduling jobs from multiple users,Running Hadoop in the cloud,Introducing Amazon Web Services,Setting up AWS,Setting up Hadoop on EC2,Runnign MapReduce on EC2,Managing your EC2 instances,Amazon Elastic MapReduce and other AWS, Pig.
  • Scripts,Hive and the Hadoop herd,Cloud Architecture,Infrastructure as a Service,Platform as a Service,Software as a Service,Benefits and Challenges,Strategic Impact,Risk Impact,Financial Impact,Requirements Analysis,Draft Architecture,Application Inventory,Service Components,User Profiles,End-to-end Design,Connectivity,Resilience,Security,Transition Management,Migration,Employee Changes.
  • Service Management,Google App Engine, Microsoft Windows,Azure, Amazon Web Services, and Other,Platform Options,Browser Interface

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Native Clients,Presentation Optimization, Real-Time Web, Authentication,Personalization, Network and Application Integration, Storage, Relational and Non-Relational Data, Reliability and Elasticity, Marketing,Payments, Development, Testing, and Staging,Production,Configuration, Administration and Troubleshooting, Refinement.

  • Cloud Computing , Consuming Cloud Services, Business Drivers & Benefits of moving to the Cloud, Cloud Service Providers & Platforms, Accountability Scalability Worst-case scenarios and Fall-back plans, Cloud Security, Creating own Cloud Services.
  • Advanced web technologies (AJAX and Mashup), distributed computing models, technologies: Hadoop and MapReduce, Infrastructure-as-a-Service (IaaS), Software as a Service (SaaS), Platform-as-a-Service (PaaS), Virtualization, Parallelization, Security, Issues in cloud computing, Distributed Computing:, Trends of computing, Introduction to distributed computing.
  • Next big thing: cloud computing, Cloud Computing:, Service models, Deployment models , IaaS, Resource Virtualization, Server, Storage, Network ,, PaaS, Cloud platform & Management Computation Storage Software as a Service (SaaS) SaaS Web services, Web 2.0, Web OS, Cloud issues and challenges, Cloud provider Lock-in, Security.
  • Service & Deployment Models,Infrastructure,Consumer View,Security and Scenarios,Dynamic Interactions and Computing Architectures,SaaS Interaction Dynamics and Software Stack Control,PaaS Dynamics and Software Stack Control,Economics of Cloud Computing,Cloud Computing Cost Analysis.
  • Cloud Computing: fault tolerance ,load balancing network,web server,enterprise bean server ,data base server,non relational solutions ,Lucene ,Map,Reduce
  • Cloud Computing Securit Cloud computing ,Security ,Service models for cloud computing,Virtualization,Storage ,Management,Data processing,Fundamental security principles,Cloud Computing Concepts,Orientation, Introduction to Clouds, MapReduce,Gossip, Membership, and Grids,P2P Systems,Key-Value Stores, Time, and Ordering,Classical Distributed Algorithms,Concurrency and Replication Control,Emerging Paradigms,Classical Systems,Real-Life Behaviors,Spark, Hortonworks, HDFS, CAP,Large Scale Data Storage,Streaming Systems,Graph Processing and Machine Learning

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