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3/12/2013 Computer Engg, IIT(BHU) 1 CLOUD COMPUTING-2

3/12/2013Computer Engg, IIT(BHU)1 CLOUD COMPUTING-2

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Service and Deployment Model Service Delivery Models  IaaS, Computing as Whole on demand e.g. google doc, facebook, SalesForce, BaseCamp, etc.  PaaS, Computing platform to built and run own Applications on cloud e.g AWS Elastic Beanstalk, Cloud Foundry, Heroku, Force.com, EngineYard, Mendix, Google App Engine etc.  SaaS, services and Applications accesses with simple web browser on demand e.g Amazon EC2, Windows Azure Virtual Machines, DynDNS, Google Compute Engine etc.

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Page 1: 3/12/2013Computer Engg, IIT(BHU)1 CLOUD COMPUTING-2

3/12/2013 Computer Engg, IIT(BHU) 1

CLOUD COMPUTING-2

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Cloud Computing Cloud computing is indeed a revolution. delivers IT solution as a service. Internet-based computing, shared resources are provided like electricity

distributed on the electrical grid. collective computing power on a single system. allocation of resources on demand. resources are used as an aggregated virtual

computer. This amalgamated configuration provides an

environment where applications execute independently without regard for any particular configuration.

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Service and Deployment Model Service Delivery Models

IaaS, Computing as Whole on demand e.g. google doc, facebook, SalesForce, BaseCamp, etc.

PaaS, Computing platform to built and run own Applications on cloud e.g AWS Elastic Beanstalk, Cloud Foundry, Heroku, Force.com, EngineYard, Mendix, Google App Engine etc.

SaaS, services and Applications accesses with simple web browser on demand e.g Amazon EC2, Windows Azure Virtual Machines, DynDNS, Google Compute Engine etc.

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Deployment Models Public Cloud

available to the general public or a large industry group Private Cloud

exist within your company's firewall and are managed by your organization.

They are cloud services you create and control within your enterprise.

Hybrid Cloud combination of the public and the private cloud using services

that are in both the public and private space. Management responsibilities are divided between the public

cloud provider and the business itself.

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Cloud Advantages

Reduced cost: Cloud computing can reduce both capital expense (CapEx) and operating expense (OpEx) costs because resources are only acquired when needed and are only paid for when used.

Refined usage of personnel: Using cloud computing frees valuable personnel allowing them to focus on delivering value rather than maintaining hardware and software.

Robust scalability: Cloud computing allows for immediate scaling, either up or down, at any time without long-term commitment.

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Utility Computing

The computing ability to meter the offered services and charge customers for exact usage.

the term originates from public utility services such as electricity.

Utility computing is a good choice for less resource demanding applications where peak usage is expected to be sporadic and rare.

Utility computing does not require Cloud computing and it can be done in any server environment.

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Utility computing Characteristics • Accountable and chargeable

– Alignment with business needs– Detailed usage– Detailed cost reporting and chargeback

• Managed service levels – Reliable, just-in-time provisioning– Adapts to business needs– Automated (not automatic)

Shared resources Optimized utilization Reduced operational costs Pooling, virtualization and provisioning

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Grid computing A Grid is a hardware and software infrastructure that

provides dependable, consistent, pervasive and inexpensive access unlike supercomputers to high end computational capabilities.

heterogeneous resources (based on different platforms, hardware/software architectures, and computer languages),

located in different places belonging to different administrative domains

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Type of Grid Computational Grid

It focuses primarily on computationally intensive operations

Data Grid It focuses on large amount of distributed data

Equipment Grid It has a primary piece of equipment e.g. telescope

and surrounding grid is used to control the equipment remotely and to analyze the data produced.

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Characteristics of Grid Computing Large scale Geographical distribution Heterogeneity Resource sharing

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Large scale: a grid must be able to deal with a number of resources ranging from just a few to millions. This raises the very serious problem of avoiding potential performance degradation as the grid size increases.

Geographical distribution: grid’s resources may be located at distant places.

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Heterogeneity: a grid hosts both software and hardware resources that can be very varied ranging from data, files, software components or programs to sensors, scientific instruments, display devices, personal digital organizers, computers, super-computers and networks.

Resource sharing: resources in a grid belong to many different organizations that allow other organizations (i.e. users) to access them.

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Grid Vs Cloud

Pervasive access: the grid must grant access to available resources by adapting to a dynamic environment in which resource failure is commonplace.

This does not imply that resources are veryewhere or universally available but that the grid must tailor its behavior as to extract the maximum performance from the available re-sources.

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Cluster A group of tightly coupled computers that work

together closely, so that in many respects they can be viewed as though they are a single computer.

deployed to improve performance and/or availability. A type of parallel or distributed processing system, collection of interconnected stand-alone computers

working together as a single, integrated computing resource.

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Cluster Computer Architecture

The work perform by cluster computer is called cluster Computing

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Characteristics of cluster

A basic cluster has the following characteristics: Multiple computing nodes,

low cost a fully functioning computer with its own memory,

CPU, possibly storage own instance of operating system

computing nodes are connected by interconnects typically low cost, high bandwidth and low latency

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permanent, high performance data storage a resource manager to distribute and schedule jobs the middleware that allows the computers act as a

distributed or parallel system parallel applications designed to run on it

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Types of Clusters

High Performance and High Throughput Clusters. used for applications which require high computing

capability High Availability Clusters

The aim is to keep the overall services of the cluster available as much as possible, considering the fail possibility of each hardware of software.

provide redundant services across multiple systems, to overcome loss of service.

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Classification of Clusters Computers Clusters can be classified according to the node type

as homogeneous clusters and heterogeneous clusters.

 Homogeneous clusters: In homogeneous clusters all nodes have similar properties. Each node is much like any other. Amount of memory and interconnects are similar.

Heterogeneous clusters: Nodes have different characteristics, in the sense of memory and interconnect performance.

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Single level (single-tier) clusters: There is no hierarchy of nodes is defined. Any node may be used for any purpose. The main advantage of the single tier cluster is its simplicity. The main disadvantage is its limit to be expanded.

Multi level (multi-tier) clusters: There is a hierarchy between nodes. There are node sets, where each set has a specialized function